Query Language
Dgraph’s GraphQL+- is based on Facebook’s GraphQL. GraphQL wasn’t developed for Graph databases, but it’s graph-like query syntax, schema validation and subgraph shaped response make it a great language choice. We’ve modified the language to better support graph operations, adding and removing features to get the best fit for graph databases. We’re calling this simplified, feature rich language, “GraphQL+-”.
GraphQL+- is a work in progress. We’re adding more features and we might further simplify existing ones.
Take a Tour - https://tour.dgraph.io
This document is the Dgraph query reference material. It is not a tutorial. It’s designed as a reference for users who already know how to write queries in GraphQL+- but need to check syntax, or indices, or functions, etc.
Running examples
The examples in this reference use a database of 21 million triples about movies and actors. The example queries run and return results. The queries are executed by an instance of Dgraph running at https://play.dgraph.io/. To run the queries locally or experiment a bit more, see the Getting Started guide, which also shows how to load the datasets used in the examples here.
GraphQL+- Fundamentals
A GraphQL+- query finds nodes based on search criteria, matches patterns in a graph and returns a graph as a result.
A query is composed of nested blocks, starting with a query root. The root finds the initial set of nodes against which the following graph matching and filtering is applied.
Returning Values
Each query has a name, specified at the query root, and the same name identifies the results.
If an edge is of a value type, the value can be returned by giving the edge name.
Query Example: In the example dataset, edges that link movies to directors and actors, movies have a name, release date and identifiers for a number of well known movie databases. This query, with name bladerunner, and root matching a movie name, returns those values for the early 80’s sci-fi classic “Blade Runner”.
{
bladerunner(func: eq([email protected], "Blade Runner")) {
uid
[email protected]
initial_release_date
netflix_id
}
}curl localhost:8080/query -XPOST -d '
{
bladerunner(func: eq([email protected], "Blade Runner")) {
uid
[email protected]
initial_release_date
netflix_id
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}The query first searches the graph, using indexes to make the search efficient, for all nodes with a name edge equalling “Blade Runner”. For the found node the query then returns the listed outgoing edges.
Every node had a unique 64 bit identifier. The uid edge in the query above returns that identifier. If the required node is already known, then the function uid finds the node.
Query Example: “Blade Runner” movie data found by UID.
{
bladerunner(func: uid(0x146a6)) {
uid
[email protected]
initial_release_date
netflix_id
}
}curl localhost:8080/query -XPOST -d '
{
bladerunner(func: uid(0x146a6)) {
uid
[email protected]
initial_release_date
netflix_id
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}A query can match many nodes and return the values for each.
Query Example: All nodes that have either “Blade” or “Runner” in the name.
{
bladerunner(func: anyofterms([email protected], "Blade Runner")) {
uid
[email protected]
initial_release_date
netflix_id
}
}curl localhost:8080/query -XPOST -d '
{
bladerunner(func: anyofterms([email protected], "Blade Runner")) {
uid
[email protected]
initial_release_date
netflix_id
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Multiple IDs can be specified in a list to the uid function.
Query Example:
{
movies(func: uid(0x146a6, 0x34a7c)) {
uid
[email protected]
initial_release_date
netflix_id
}
}curl localhost:8080/query -XPOST -d '
{
movies(func: uid(0x146a6, 0x34a7c)) {
uid
[email protected]
initial_release_date
netflix_id
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}If your predicate has special characters, then you should wrap it with angular
brackets while asking for it in the query. E.g. <first:name>
Expanding Graph Edges
A query expands edges from node to node by nesting query blocks with { }.
Query Example: The actors and characters played in “Blade Runner”. The query first finds the node with name “Blade Runner”, then follows outgoing starring edges to nodes representing an actor’s performance as a character. From there the performance.actor and performance,character edges are expanded to find the actor names and roles for every actor in the movie.
{
brCharacters(func: eq([email protected], "Blade Runner")) {
[email protected]
initial_release_date
starring {
performance.actor {
[email protected] # actor name
}
performance.character {
[email protected] # character name
}
}
}
}curl localhost:8080/query -XPOST -d '
{
brCharacters(func: eq([email protected], "Blade Runner")) {
[email protected]
initial_release_date
starring {
performance.actor {
[email protected] # actor name
}
performance.character {
[email protected] # character name
}
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Comments
Anything on a line following a # is a comment
Applying Filters
The query root finds an initial set of nodes and the query proceeds by returning values and following edges to further nodes - any node reached in the query is found by traversal after the search at root. The nodes found can be filtered by applying @filter, either after the root or at any edge.
Query Example: “Blade Runner” director Ridley Scott’s movies released before the year 2000.
{
scott(func: eq([email protected], "Ridley Scott")) {
[email protected]
initial_release_date
director.film @filter(le(initial_release_date, "2000")) {
[email protected]
initial_release_date
}
}
}curl localhost:8080/query -XPOST -d '
{
scott(func: eq([email protected], "Ridley Scott")) {
[email protected]
initial_release_date
director.film @filter(le(initial_release_date, "2000")) {
[email protected]
initial_release_date
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Query Example: Movies with either “Blade” or “Runner” in the title and released before the year 2000.
{
bladerunner(func: anyofterms([email protected], "Blade Runner")) @filter(le(initial_release_date, "2000")) {
uid
[email protected]
initial_release_date
netflix_id
}
}curl localhost:8080/query -XPOST -d '
{
bladerunner(func: anyofterms([email protected], "Blade Runner")) @filter(le(initial_release_date, "2000")) {
uid
[email protected]
initial_release_date
netflix_id
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Language Support
A @lang directive must be specified in the schema to query or mutate
predicates with language tags.
Dgraph supports UTF-8 strings.
In a query, for a string valued edge edge, the syntax
[email protected]:...:langN
specifies the preference order for returned languages, with the following rules.
- At most one result will be returned.
- The preference list is considered left to right: if a value in given language is not found, the next language from the list is considered.
- If there are no values in any of the specified languages, no value is returned.
- A final
.means that a value without a specified language is returned or if there is no value without language, a value in “some” language is returned.
For example:
name=> Look for an untagged string; return nothing if no untagged value exits.[email protected]=> Look for an untagged string, then any language.[email protected]=> Look forentagged string; return nothing if noentagged string exists.[email protected]:.=> Look foren, then untagged, then any language.[email protected]:pl=> Look foren, thenpl, otherwise nothing.[email protected]:pl:.=> Look foren, thenpl, then untagged, then any language.
. notation and attribute name without language tag works as described above.
alloftext, anyoftext), when no language is specified, default (English) Full Text Search tokenizer is used.
Query Example: Some of Bollywood director and actor Farhan Akhtar’s movies have a name stored in Russian as well as Hindi and English, others do not.
{
q(func: allofterms([email protected], "Farhan Akhtar")) {
[email protected]
[email protected]
director.film {
[email protected]:hi:en
[email protected]
[email protected]
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
q(func: allofterms([email protected], "Farhan Akhtar")) {
[email protected]
[email protected]
director.film {
[email protected]:hi:en
[email protected]
[email protected]
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Functions
Functions allow filtering based on properties of nodes or variables. Functions can be applied in the query root or in filters.
For functions on string valued predicates, if no language preference is given, the function is applied to all languages and strings without a language tag; if a language preference is given, the function is applied only to strings of the given language.
Term matching
allofterms
Syntax Example: allofterms(predicate, "space-separated term list")
Schema Types: string
Index Required: term
Matches strings that have all specified terms in any order; case insensitive.
Usage at root
Query Example: All nodes that have name containing terms indiana and jones, returning the english name and genre in english.
{
me(func: allofterms([email protected], "jones indiana")) {
[email protected]
genre {
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
me(func: allofterms([email protected], "jones indiana")) {
[email protected]
genre {
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Usage as Filter
Query Example: All Steven Spielberg films that contain the words indiana and jones. The @filter(has(director.film)) removes nodes with name Steven Spielberg that aren’t the director — the data also contains a character in a film called Steven Spielberg.
{
me(func: eq([email protected], "Steven Spielberg")) @filter(has(director.film)) {
[email protected]
director.film @filter(allofterms([email protected], "jones indiana")) {
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
me(func: eq([email protected], "Steven Spielberg")) @filter(has(director.film)) {
[email protected]
director.film @filter(allofterms([email protected], "jones indiana")) {
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}anyofterms
Syntax Example: anyofterms(predicate, "space-separated term list")
Schema Types: string
Index Required: term
Matches strings that have any of the specified terms in any order; case insensitive.
Usage at root
Query Example: All nodes that have a name containing either poison or peacock. Many of the returned nodes are movies, but people like Joan Peacock also meet the search terms because without a cascade directive the query doesn’t require a genre.
{
me(func:anyofterms([email protected], "poison peacock")) {
[email protected]
genre {
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
me(func:anyofterms([email protected], "poison peacock")) {
[email protected]
genre {
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Usage as filter
Query Example: All Steven Spielberg movies that contain war or spies. The @filter(has(director.film)) removes nodes with name Steven Spielberg that aren’t the director — the data also contains a character in a film called Steven Spielberg.
{
me(func: eq([email protected], "Steven Spielberg")) @filter(has(director.film)) {
[email protected]
director.film @filter(anyofterms([email protected], "war spies")) {
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
me(func: eq([email protected], "Steven Spielberg")) @filter(has(director.film)) {
[email protected]
director.film @filter(anyofterms([email protected], "war spies")) {
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Regular Expressions
Syntax Examples: regexp(predicate, /regular-expression/) or case insensitive regexp(predicate, /regular-expression/i)
Schema Types: string
Index Required: trigram
Matches strings by regular expression. The regular expression language is that of go regular expressions.
Query Example: At root, match nodes with Steven Sp at the start of name, followed by any characters. For each such matched uid, match the films containing ryan. Note the difference with allofterms, which would match only ryan but regular expression search will also match within terms, such as bryan.
{
directors(func: regexp([email protected], /^Steven Sp.*$/)) {
[email protected]
director.film @filter(regexp([email protected], /ryan/i)) {
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
directors(func: regexp([email protected], /^Steven Sp.*$/)) {
[email protected]
director.film @filter(regexp([email protected], /ryan/i)) {
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Technical details
A Trigram is a substring of three continuous runes. For example, Dgraph has trigrams Dgr, gra, rap, aph.
To ensure efficiency of regular expression matching, Dgraph uses trigram indexing. That is, Dgraph converts the regular expression to a trigram query, uses the trigram index and trigram query to find possible matches and applies the full regular expression search only to the possibles.
Writing Efficient Regular Expressions and Limitations
Keep the following in mind when designing regular expression queries.
- At least one trigram must be matched by the regular expression (patterns shorter than 3 runes are not supported). That is, Dgraph requires regular expressions that can be converted to a trigram query.
- The number of alternative trigrams matched by the regular expression should be as small as possible (
[a-zA-Z][a-zA-Z][0-9]is not a good idea). Many possible matches means the full regular expression is checked against many strings; where as, if the expression enforces more trigrams to match, Dgraph can make better use of the index and check the full regular expression against a smaller set of possible matches. - Thus, the regular expression should be as precise as possible. Matching longer strings means more required trigrams, which helps to effectively use the index.
- If repeat specifications (
*,+,?,{n,m}) are used, the entire regular expression must not match the empty string or any string: for example,*may be used like[Aa]bcd*but not like(abcd)*or(abcd)|((defg)*) - Repeat specifications after bracket expressions (e.g.
[fgh]{7},[0-9]+or[a-z]{3,5}) are often considered as matching any string because they match too many trigrams. - If the partial result (for subset of trigrams) exceeds 1000000 uids during index scan, the query is stopped to prohibit expensive queries.
Full Text Search
Syntax Examples: alloftext(predicate, "space-separated text") and anyoftext(predicate, "space-separated text")
Schema Types: string
Index Required: fulltext
Apply full text search with stemming and stop words to find strings matching all or any of the given text.
The following steps are applied during index generation and to process full text search arguments:
- Tokenization (according to Unicode word boundaries).
- Conversion to lowercase.
- Unicode-normalization (to Normalization Form KC).
- Stemming using language-specific stemmer.
- Stop words removal
Dgraph uses bleve for its full text search indexing. See also the bleve language specific stop word lists.
Following table contains all supported languages and corresponding country-codes.
| Language | Country Code |
|---|---|
| Danish | da |
| Dutch | nl |
| English | en |
| Finnish | fi |
| French | fr |
| German | de |
| Hungarian | hu |
| Italian | it |
| Norwegian | no |
| Portuguese | pt |
| Romanian | ro |
| Russian | ru |
| Spanish | es |
| Swedish | sv |
| Turkish | tr |
| Chinese | zh |
| Japanese | ja |
| Korean | ko |
Query Example: All names that have run, running, etc and man. Stop word removal eliminates the and maybe
{
movie(func:alloftext([email protected], "the man maybe runs")) {
[email protected]
}
}curl localhost:8080/query -XPOST -d '
{
movie(func:alloftext([email protected], "the man maybe runs")) {
[email protected]
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Inequality
equal to
Syntax Examples:
eq(predicate, value)eq(val(varName), value)eq(predicate, val(varName))eq(count(predicate), value)eq(predicate, [val1, val2, ..., valN])
Schema Types: int, float, bool, string, dateTime
Index Required: An index is required for the eq(predicate, ...) forms (see table below). For count(predicate) at the query root, the @count index is required. For variables the values have been calculated as part of the query, so no index is required.
| Type | Index Options |
|---|---|
int |
int |
float |
float |
bool |
bool |
string |
exact, hash |
dateTime |
dateTime |
Test for equality of a predicate or variable to a value or find in a list of values.
The boolean constants are true and false, so with eq this becomes, for example, eq(boolPred, true).
Query Example: Movies with exactly thirteen genres.
{
me(func: eq(count(genre), 13)) {
[email protected]
genre {
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
me(func: eq(count(genre), 13)) {
[email protected]
genre {
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Query Example: Directors called Steven who have directed 1,2 or 3 movies.
{
steve as var(func: allofterms([email protected], "Steven")) {
films as count(director.film)
}
stevens(func: uid(steve)) @filter(eq(val(films), [1,2,3])) {
[email protected]
numFilms : val(films)
}
}curl localhost:8080/query -XPOST -d '
{
steve as var(func: allofterms([email protected], "Steven")) {
films as count(director.film)
}
stevens(func: uid(steve)) @filter(eq(val(films), [1,2,3])) {
[email protected]
numFilms : val(films)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}less than, less than or equal to, greater than and greater than or equal to
Syntax Examples: for inequality IE
IE(predicate, value)IE(val(varName), value)IE(predicate, val(varName))IE(count(predicate), value)
With IE replaced by
leless than or equal toltless thangegreater than or equal togtgreather than
Schema Types: int, float, string, dateTime
Index required: An index is required for the IE(predicate, ...) forms (see table below). For count(predicate) at the query root, the @count index is required. For variables the values have been calculated as part of the query, so no index is required.
| Type | Index Options |
|---|---|
int |
int |
float |
float |
string |
exact |
dateTime |
dateTime |
Query Example: Ridley Scott movies released before 1980.
{
me(func: eq([email protected], "Ridley Scott")) {
[email protected]
director.film @filter(lt(initial_release_date, "1980-01-01")) {
initial_release_date
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
me(func: eq([email protected], "Ridley Scott")) {
[email protected]
director.film @filter(lt(initial_release_date, "1980-01-01")) {
initial_release_date
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Query Example: Movies with directors with Steven in name and have directed more than 100 actors.
{
ID as var(func: allofterms([email protected], "Steven")) {
director.film {
num_actors as count(starring)
}
total as sum(val(num_actors))
}
dirs(func: uid(ID)) @filter(gt(val(total), 100)) {
[email protected]
total_actors : val(total)
}
}curl localhost:8080/query -XPOST -d '
{
ID as var(func: allofterms([email protected], "Steven")) {
director.film {
num_actors as count(starring)
}
total as sum(val(num_actors))
}
dirs(func: uid(ID)) @filter(gt(val(total), 100)) {
[email protected]
total_actors : val(total)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Query Example: A movie in each genre that has over 30000 movies. Because there is no order specified on genres, the order will be by UID. The count index records the number of edges out of nodes and makes such queries more .
{
genre(func: gt(count(~genre), 30000)){
[email protected]
~genre (first:1) {
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
genre(func: gt(count(~genre), 30000)){
[email protected]
~genre (first:1) {
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Query Example: Directors called Steven and their movies which have initial_release_date greater
than that of the movie Minority Report.
{
var(func: eq([email protected],"Minority Report")) {
d as initial_release_date
}
me(func: eq([email protected], "Steven Spielberg")) {
[email protected]
director.film @filter(ge(initial_release_date, val(d))) {
initial_release_date
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
var(func: eq([email protected],"Minority Report")) {
d as initial_release_date
}
me(func: eq([email protected], "Steven Spielberg")) {
[email protected]
director.film @filter(ge(initial_release_date, val(d))) {
initial_release_date
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}uid
Syntax Examples:
q(func: uid(<uid>))predicate @filter(uid(<uid1>, ..., <uidn>))predicate @filter(uid(a))for variableaq(func: uid(a,b))for variablesaandb
Filters nodes at the current query level to only nodes in the given set of UIDs.
For query variable a, uid(a) represents the set of UIDs stored in a. For value variable b, uid(b) represents the UIDs from the UID to value map. With two or more variables, uid(a,b,...) represents the union of all the variables.
Query Example: If the UID of a node is known, values for the node can be read directly. The films of Priyanka Chopra by known UID
{
films(func: uid(0xcceb)) {
[email protected]
actor.film {
performance.film {
[email protected]
}
}
}
}curl localhost:8080/query -XPOST -d '
{
films(func: uid(0xcceb)) {
[email protected]
actor.film {
performance.film {
[email protected]
}
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Query Example: The films of Taraji Henson by genre.
{
var(func: allofterms([email protected], "Taraji Henson")) {
actor.film {
F as performance.film {
G as genre
}
}
}
Taraji_films_by_genre(func: uid(G)) {
genre_name : [email protected]
films : ~genre @filter(uid(F)) {
film_name : [email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
var(func: allofterms([email protected], "Taraji Henson")) {
actor.film {
F as performance.film {
G as genre
}
}
}
Taraji_films_by_genre(func: uid(G)) {
genre_name : [email protected]
films : ~genre @filter(uid(F)) {
film_name : [email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Query Example: Taraji Henson films ordered by numer of genres, with genres listed in order of how many films Taraji has made in each genre.
{
var(func: allofterms([email protected], "Taraji Henson")) {
actor.film {
F as performance.film {
G as count(genre)
genre {
C as count(~genre @filter(uid(F)))
}
}
}
}
Taraji_films_by_genre_count(func: uid(G), orderdesc: val(G)) {
film_name : [email protected]
genres : genre (orderdesc: val(C)) {
genre_name : [email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
var(func: allofterms([email protected], "Taraji Henson")) {
actor.film {
F as performance.film {
G as count(genre)
genre {
C as count(~genre @filter(uid(F)))
}
}
}
}
Taraji_films_by_genre_count(func: uid(G), orderdesc: val(G)) {
film_name : [email protected]
genres : genre (orderdesc: val(C)) {
genre_name : [email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}uid_in
Syntax Examples:
q(func: ...) @filter(uid_in(predicate, <uid>)predicate1 @filter(uid_in(predicate2, <uid>)
Schema Types: UID
Index Required: none
While the uid function filters nodes at the current level based on UID, function uid_in allows looking ahead along an edge to check that it leads to a particular UID. This can often save an extra query block and avoids returning the edge.
uid_in cannot be used at root, it accepts one UID constant as its argument (not a variable).
Query Example: The collaborations of Marc Caro and Jean-Pierre Jeunet (UID 597046). If the UID of Jean-Pierre Jeunet is known, querying this way removes the need to have a block extracting his UID into a variable and the extra edge traversal and filter for ~director.film.
{
caro(func: eq([email protected], "Marc Caro")) {
[email protected]
director.film @filter(uid_in(~director.film, 597046)){
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
caro(func: eq([email protected], "Marc Caro")) {
[email protected]
director.film @filter(uid_in(~director.film, 597046)){
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}has
Syntax Examples: has(predicate)
Schema Types: all
Determines if a node has a particular predicate.
Query Example: First five directors and all their movies that have a release date recorded. Directors have directed at least one film — equivalent semantics to gt(count(director.film), 0).
{
me(func: has(director.film), first: 5) {
[email protected]
director.film @filter(has(initial_release_date)) {
initial_release_date
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
me(func: has(director.film), first: 5) {
[email protected]
director.film @filter(has(initial_release_date)) {
initial_release_date
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Geolocation
Note that for geo queries, any polygon with holes is replace with the outer loop, ignoring holes. Also, as for version 0.7.7 polygon containment checks are approximate.
Mutations
To make use of the geo functions you would need an index on your predicate.
loc: geo @index(geo) .
Here is how you would add a Point.
{
set {
<_:0xeb1dde9c> <loc> "{'type':'Point','coordinates':[-122.4220186,37.772318]}"^^<geo:geojson> .
<_:0xeb1dde9c> <name> "Hamon Tower" .
}
}
Here is how you would associate a Polygon with a node. Adding a MultiPolygon is also similar.
{
set {
<_:0xf76c276b> <loc> "{'type':'Polygon','coordinates':[[[-122.409869,37.7785442],[-122.4097444,37.7786443],[-122.4097544,37.7786521],[-122.4096334,37.7787494],[-122.4096233,37.7787416],[-122.4094004,37.7789207],[-122.4095818,37.7790617],[-122.4097883,37.7792189],[-122.4102599,37.7788413],[-122.409869,37.7785442]],[[-122.4097357,37.7787848],[-122.4098499,37.778693],[-122.4099025,37.7787339],[-122.4097882,37.7788257],[-122.4097357,37.7787848]]]}"^^<geo:geojson> .
<_:0xf76c276b> <name> "Best Western Americana Hotel" .
}
}
The above examples have been picked from our SF Tourism dataset.
Query
near
Syntax Example: near(predicate, [long, lat], distance)
Schema Types: geo
Index Required: geo
Matches all entities where the location given by predicate is within distance metres of geojson coordinate [long, lat].
Query Example: Tourist destinations within 1 kilometer of a point in Golden Gate Park, San Fransico.
{
tourist(func: near(loc, [-122.469829, 37.771935], 1000) ) {
name
}
}curl localhost:8080/query -XPOST -d '
{
tourist(func: near(loc, [-122.469829, 37.771935], 1000) ) {
name
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}within
Syntax Example: within(predicate, [[[long1, lat1], ..., [longN, latN]]])
Schema Types: geo
Index Required: geo
Matches all entities where the location given by predicate lies within the polygon specified by the geojson coordinate array.
Query Example: Tourist destinations within the specified area of Golden Gate Park, San Fransico.
{
tourist(func: within(loc, [[[-122.47266769409178, 37.769018558337926 ], [ -122.47266769409178, 37.773699921075135 ], [ -122.4651575088501, 37.773699921075135 ], [ -122.4651575088501, 37.769018558337926 ], [ -122.47266769409178, 37.769018558337926]]] )) {
name
}
}curl localhost:8080/query -XPOST -d '
{
tourist(func: within(loc, [[[-122.47266769409178, 37.769018558337926 ], [ -122.47266769409178, 37.773699921075135 ], [ -122.4651575088501, 37.773699921075135 ], [ -122.4651575088501, 37.769018558337926 ], [ -122.47266769409178, 37.769018558337926]]] )) {
name
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}contains
Syntax Examples: contains(predicate, [long, lat]) or contains(predicate, [[long1, lat1], ..., [longN, latN]])
Schema Types: geo
Index Required: geo
Matches all entities where the polygon describing the location given by predicate contains geojson coordinate [long, lat] or given geojson polygon.
Query Example : All entities that contain a point in the flamingo enclosure of San Fransico Zoo.
{
tourist(func: contains(loc, [ -122.50326097011566, 37.73353615592843 ] )) {
name
}
}curl localhost:8080/query -XPOST -d '
{
tourist(func: contains(loc, [ -122.50326097011566, 37.73353615592843 ] )) {
name
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}intersects
Syntax Example: intersects(predicate, [[[long1, lat1], ..., [longN, latN]]])
Schema Types: geo
Index Required: geo
Matches all entities where the polygon describing the location given by predicate intersects the given geojson polygon.
{
tourist(func: intersects(loc, [[[-122.503325343132, 37.73345766902749 ], [ -122.503325343132, 37.733903134117966 ], [ -122.50271648168564, 37.733903134117966 ], [ -122.50271648168564, 37.73345766902749 ], [ -122.503325343132, 37.73345766902749]]] )) {
name
}
}curl localhost:8080/query -XPOST -d '
{
tourist(func: intersects(loc, [[[-122.503325343132, 37.73345766902749 ], [ -122.503325343132, 37.733903134117966 ], [ -122.50271648168564, 37.733903134117966 ], [ -122.50271648168564, 37.73345766902749 ], [ -122.503325343132, 37.73345766902749]]] )) {
name
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Connecting Filters
Within @filter multiple functions can be used with boolean connectives.
AND, OR and NOT
Connectives AND, OR and NOT join filters and can be built into arbitrarily complex filters, such as (NOT A OR B) AND (C AND NOT (D OR E)). Note that, NOT binds more tightly than AND which binds more tightly than OR.
Query Example : All Steven Spielberg movies that contain either both “indiana” and “jones” OR both “jurassic” and “park”.
{
me(func: eq([email protected], "Steven Spielberg")) @filter(has(director.film)) {
[email protected]
director.film @filter(allofterms([email protected], "jones indiana") OR allofterms([email protected], "jurassic park")) {
uid
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
me(func: eq([email protected], "Steven Spielberg")) @filter(has(director.film)) {
[email protected]
director.film @filter(allofterms([email protected], "jones indiana") OR allofterms([email protected], "jurassic park")) {
uid
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Alias
Syntax Examples:
aliasName : predicatealiasName : predicate { ... }aliasName : varName as ...aliasName : count(predicate)aliasName : max(val(varName))
An alias provides an alternate name in results. Predicates, variables and aggregates can be aliased by prefixing with the alias name and :. Aliases do not have to be different to the original predicate name, but, within a block, an alias must be distinct from predicate names and other aliases returned in the same block. Aliases can be used to return the same predicate multiple times within a block.
Query Example: Directors with name matching term Steven, their UID, english name, average number of actors per movie, total number of films and the name of each film in english and french.
{
ID as var(func: allofterms([email protected], "Steven")) @filter(has(director.film)) {
director.film {
num_actors as count(starring)
}
average as avg(val(num_actors))
}
films(func: uid(ID)) {
director_id : uid
english_name : [email protected]
average_actors : val(average)
num_films : count(director.film)
films : director.film {
name : [email protected]
english_name : [email protected]
french_name : [email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
ID as var(func: allofterms([email protected], "Steven")) @filter(has(director.film)) {
director.film {
num_actors as count(starring)
}
average as avg(val(num_actors))
}
films(func: uid(ID)) {
director_id : uid
english_name : [email protected]
average_actors : val(average)
num_films : count(director.film)
films : director.film {
name : [email protected]
english_name : [email protected]
french_name : [email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Pagination
Pagination allows returning only a portion, rather than the whole, result set. This can be useful for top-k style queries as well as to reduce the size of the result set for client side processing or to allow paged access to results.
Pagination is often used with sorting.
uid, which is assigned randomly. So the ordering, while deterministic, might not be what you expected.
First
Syntax Examples:
q(func: ..., first: N)predicate (first: N) { ... }predicate @filter(...) (first: N) { ... }
For positive N, first: N retrieves the first N results, by sorted or UID order.
For negative N, first: N retrieves the last N results, by sorted or UID order. Currently, negative is only supported when no order is applied. To achieve the effect of a negative with a sort, reverse the order of the sort and use a positive N.
Query Example: Last two films, by UID order, directed by Steven Spielberg and the first 3 genres, sorted alphabetically by English name, of those movies.
{
me(func: allofterms([email protected], "Steven Spielberg")) {
director.film (first: -2) {
[email protected]
initial_release_date
genre (orderasc: [email protected]) (first: 3) {
[email protected]
}
}
}
}curl localhost:8080/query -XPOST -d '
{
me(func: allofterms([email protected], "Steven Spielberg")) {
director.film (first: -2) {
[email protected]
initial_release_date
genre (orderasc: [email protected]) (first: 3) {
[email protected]
}
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Query Example: The three directors with name Steven who have directed the most actors of all directors named Steven.
{
ID as var(func: allofterms([email protected], "Steven")) @filter(has(director.film)) {
director.film {
stars as count(starring)
}
totalActors as sum(val(stars))
}
mostStars(func: uid(ID), orderdesc: val(totalActors), first: 3) {
[email protected]
stars : val(totalActors)
director.film {
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
ID as var(func: allofterms([email protected], "Steven")) @filter(has(director.film)) {
director.film {
stars as count(starring)
}
totalActors as sum(val(stars))
}
mostStars(func: uid(ID), orderdesc: val(totalActors), first: 3) {
[email protected]
stars : val(totalActors)
director.film {
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Offset
Syntax Examples:
q(func: ..., offset: N)predicate (offset: N) { ... }predicate (first: M, offset: N) { ... }predicate @filter(...) (offset: N) { ... }
With offset: N the first N results are not returned. Used in combination with first, first: M, offset: N skips over N results and returns the following M.
Query Example: Order Hark Tsui’s films by English title, skip over the first 4 and return the following 6.
{
me(func: allofterms([email protected], "Hark Tsui")) {
[email protected]
[email protected]
director.film (orderasc: [email protected]) (first:6, offset:4) {
genre {
[email protected]
}
[email protected]
[email protected]
initial_release_date
}
}
}curl localhost:8080/query -XPOST -d '
{
me(func: allofterms([email protected], "Hark Tsui")) {
[email protected]
[email protected]
director.film (orderasc: [email protected]) (first:6, offset:4) {
genre {
[email protected]
}
[email protected]
[email protected]
initial_release_date
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}After
Syntax Examples:
q(func: ..., after: UID)predicate (first: N, after: UID) { ... }predicate @filter(...) (first: N, after: UID) { ... }
Another way to get results after skipping over some results is to use the default UID ordering and skip directly past a node specified by UID. For example, a first query could be of the form predicate (after: 0x0, first: N), or just predicate (first: N), with subsequent queries of the form predicate(after: <uid of last entity in last result>, first: N).
Query Example: The first five of Baz Luhrmann’s films, sorted by UID order.
{
me(func: allofterms([email protected], "Baz Luhrmann")) {
[email protected]
director.film (first:5) {
uid
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
me(func: allofterms([email protected], "Baz Luhrmann")) {
[email protected]
director.film (first:5) {
uid
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}The fifth movie is the Australian movie classic Strictly Ballroom. It has UID 0x52753. The results after Strictly Ballroom can now be obtained with after.
{
me(func: allofterms([email protected], "Baz Luhrmann")) {
[email protected]
director.film (first:5, after: 0x52753) {
uid
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
me(func: allofterms([email protected], "Baz Luhrmann")) {
[email protected]
director.film (first:5, after: 0x52753) {
uid
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Count
Syntax Examples:
count(predicate)count(uid)
The form count(predicate) counts how many predicate edges lead out of a node.
The form count(uid) counts the number of UIDs matched in the enclosing block.
Query Example: The number of films acted in by each actor with Orlando in their name.
{
me(func: allofterms([email protected], "Orlando")) @filter(has(actor.film)) {
[email protected]
count(actor.film)
}
}curl localhost:8080/query -XPOST -d '
{
me(func: allofterms([email protected], "Orlando")) @filter(has(actor.film)) {
[email protected]
count(actor.film)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Count can be used at root and aliased.
Query Example: Count of directors who have directed more than five films. When used at the query root, the count index is required.
{
directors(func: gt(count(director.film), 5)) {
totalDirectors : count(uid)
}
}curl localhost:8080/query -XPOST -d '
{
directors(func: gt(count(director.film), 5)) {
totalDirectors : count(uid)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Count can be assigned to a value variable.
Query Example: The actors of Ang Lee’s “Eat Drink Man Woman” ordered by the number of movies acted in.
{
var(func: allofterms([email protected], "eat drink man woman")) {
starring {
actors as performance.actor {
totalRoles as count(actor.film)
}
}
}
edmw(func: uid(actors), orderdesc: val(totalRoles)) {
[email protected]
[email protected]
totalRoles : val(totalRoles)
}
}curl localhost:8080/query -XPOST -d '
{
var(func: allofterms([email protected], "eat drink man woman")) {
starring {
actors as performance.actor {
totalRoles as count(actor.film)
}
}
}
edmw(func: uid(actors), orderdesc: val(totalRoles)) {
[email protected]
[email protected]
totalRoles : val(totalRoles)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Sorting
Syntax Examples:
q(func: ..., orderasc: predicate)q(func: ..., orderdesc: val(varName))predicate (orderdesc: predicate) { ... }predicate @filter(...) (orderasc: N) { ... }q(func: ..., orderasc: predicate1, orderdesc: predicate2)
Sortable Types: int, float, String, dateTime, id, default
Results can be sorted in ascending, orderasc or decending orderdesc order by a predicate or variable.
For sorting on predicates with sortable indices, Dgraph sorts on the values and with the index in parallel and returns whichever result is computed first.
Sorted queries retrieve up to 1000 results by default. This can be changed with first.
Query Example: French director Jean-Pierre Jeunet’s movies sorted by release date.
{
me(func: allofterms([email protected], "Jean-Pierre Jeunet")) {
[email protected]
director.film(orderasc: initial_release_date) {
[email protected]
[email protected]
initial_release_date
}
}
}curl localhost:8080/query -XPOST -d '
{
me(func: allofterms([email protected], "Jean-Pierre Jeunet")) {
[email protected]
director.film(orderasc: initial_release_date) {
[email protected]
[email protected]
initial_release_date
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Sorting can be performed at root and on value variables.
Query Example: All genres sorted alphabetically and the five movies in each genre with the most genres.
{
genres as var(func: has(~genre)) {
~genre {
numGenres as count(genre)
}
}
genres(func: uid(genres), orderasc: [email protected]) {
[email protected]
~genre (orderdesc: val(numGenres), first: 5) {
[email protected]
genres : val(numGenres)
}
}
}curl localhost:8080/query -XPOST -d '
{
genres as var(func: has(~genre)) {
~genre {
numGenres as count(genre)
}
}
genres(func: uid(genres), orderasc: [email protected]) {
[email protected]
~genre (orderdesc: val(numGenres), first: 5) {
[email protected]
genres : val(numGenres)
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Sorting can also be performed by multiple predicates as shown below. If the values are equal for the first predicate, then they are sorted by the second predicate and so on.
Query Example: Find all nodes which have type Person, sort them by their first_name and among those that have the same first_name sort them by last_name in descending order.
{
me(func: eq(type, "Person", orderasc: first_name, orderdesc: last_name)) {
first_name
last_name
}
}
Multiple Query Blocks
Inside a single query, multiple query blocks are allowed. The result is all blocks with corresponding block names.
Multiple query blocks are executed in parallel.
The blocks need not be related in any way.
Query Example: All of Angelina Jolie’s films, with genres, and Peter Jackson’s films since 2008.
{
AngelinaInfo(func:allofterms([email protected], "angelina jolie")) {
[email protected]
actor.film {
performance.film {
genre {
[email protected]
}
}
}
}
DirectorInfo(func: eq([email protected], "Peter Jackson")) {
[email protected]
director.film @filter(ge(initial_release_date, "2008")) {
Release_date: initial_release_date
Name: [email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
AngelinaInfo(func:allofterms([email protected], "angelina jolie")) {
[email protected]
actor.film {
performance.film {
genre {
[email protected]
}
}
}
}
DirectorInfo(func: eq([email protected], "Peter Jackson")) {
[email protected]
director.film @filter(ge(initial_release_date, "2008")) {
Release_date: initial_release_date
Name: [email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}If queries contain some overlap in answers, the result sets are still independent
Query Example: The movies Mackenzie Crook has acted in and the movies Jack Davenport has acted in. The results sets overlap because both have acted in the Pirates of the Caribbean movies, but the results are independent and both contain the full answers sets.
{
Mackenzie(func:allofterms([email protected], "Mackenzie Crook")) {
[email protected]
actor.film {
performance.film {
uid
[email protected]
}
performance.character {
[email protected]
}
}
}
Jack(func:allofterms([email protected], "Jack Davenport")) {
[email protected]
actor.film {
performance.film {
uid
[email protected]
}
performance.character {
[email protected]
}
}
}
}curl localhost:8080/query -XPOST -d '
{
Mackenzie(func:allofterms([email protected], "Mackenzie Crook")) {
[email protected]
actor.film {
performance.film {
uid
[email protected]
}
performance.character {
[email protected]
}
}
}
Jack(func:allofterms([email protected], "Jack Davenport")) {
[email protected]
actor.film {
performance.film {
uid
[email protected]
}
performance.character {
[email protected]
}
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Var Blocks
Var blocks start with the keyword var and are not returned in the query results.
Query Example: Angelina Jolie’s movies ordered by genre.
{
var(func:allofterms([email protected], "angelina jolie")) {
[email protected]
actor.film {
A AS performance.film {
B AS genre
}
}
}
films(func: uid(B), orderasc: [email protected]) {
[email protected]
~genre @filter(uid(A)) {
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
var(func:allofterms([email protected], "angelina jolie")) {
[email protected]
actor.film {
A AS performance.film {
B AS genre
}
}
}
films(func: uid(B), orderasc: [email protected]) {
[email protected]
~genre @filter(uid(A)) {
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Query Variables
Syntax Examples:
varName as q(func: ...) { ... }varName as var(func: ...) { ... }varName as predicate { ... }varName as predicate @filter(...) { ... }
Types : uid
Nodes (UID’s) matched at one place in a query can be stored in a variable and used elsewhere. Query variables can be used in other query blocks or in a child node of the defining block.
Query variables do not affect the semantics of the query at the point of definition. Query variables are evaluated to all nodes matched by the defining block.
In general, query blocks are executed in parallel, but variables impose an evaluation order on some blocks. Cycles induced by variable dependence are not permitted.
If a variable is defined, it must be used elsewhere in the query.
A query variable is used by extracting the UIDs in it with uid(var-name).
The syntax func: uid(A,B) or @filter(uid(A,B)) means the union of UIDs for variables A and B.
Query Example: The movies of Angelia Jolie and Brad Pitt where both have acted on movies in the same genre. Note that B and D match all genres for all movies, not genres per movie.
{
var(func:allofterms([email protected], "angelina jolie")) {
actor.film {
A AS performance.film { # All films acted in by Angelina Jolie
B As genre # Genres of all the films acted in by Angelina Jolie
}
}
}
var(func:allofterms([email protected], "brad pitt")) {
actor.film {
C AS performance.film { # All films acted in by Brad Pitt
D as genre # Genres of all the films acted in by Brad Pitt
}
}
}
films(func: uid(D)) @filter(uid(B)) { # Genres from both Angelina and Brad
[email protected]
~genre @filter(uid(A, C)) { # Movies in either A or C.
[email protected]
}
}
}curl localhost:8080/query -XPOST -d '
{
var(func:allofterms([email protected], "angelina jolie")) {
actor.film {
A AS performance.film { # All films acted in by Angelina Jolie
B As genre # Genres of all the films acted in by Angelina Jolie
}
}
}
var(func:allofterms([email protected], "brad pitt")) {
actor.film {
C AS performance.film { # All films acted in by Brad Pitt
D as genre # Genres of all the films acted in by Brad Pitt
}
}
}
films(func: uid(D)) @filter(uid(B)) { # Genres from both Angelina and Brad
[email protected]
~genre @filter(uid(A, C)) { # Movies in either A or C.
[email protected]
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Value Variables
Syntax Examples:
varName as scalarPredicatevarName as count(predicate)varName as avg(...)varName as math(...)
Types : int, float, String, dateTime, id, default, geo, bool
Value variables store scalar values. Value variables are a map from the UIDs of the enclosing block to the corresponding values.
It therefor only makes sense to use the values from a value variable in a context that matches the same UIDs - if used in a block matching different UIDs the value variable is undefined.
It is an error to define a value variable but not use it elsewhere in the query.
Value variables are used by extracting the values with val(var-name), or by extracting the UIDs with uid(var-name).
Facet values can be stored in value variables.
Query Example: The number of movie roles played by the actors of the 80’s classic “The Princess Bride”. Query variable pbActors matches the UIDs of all actors from the movie. Value variable roles is thus a map from actor UID to number of roles. Value variable roles can be used in the the totalRoles query block because that query block also matches the pbActors UIDs, so the actor to number of roles map is available.
{
var(func:allofterms([email protected], "The Princess Bride")) {
starring {
pbActors as performance.actor {
roles as count(actor.film)
}
}
}
totalRoles(func: uid(pbActors), orderasc: val(roles)) {
[email protected]
numRoles : val(roles)
}
}curl localhost:8080/query -XPOST -d '
{
var(func:allofterms([email protected], "The Princess Bride")) {
starring {
pbActors as performance.actor {
roles as count(actor.film)
}
}
}
totalRoles(func: uid(pbActors), orderasc: val(roles)) {
[email protected]
numRoles : val(roles)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Value variables can be used in place of UID variables by extracting the UID list from the map.
Query Example: The same query as the previous example, but using value variable roles for matching UIDs in the totalRoles query block.
{
var(func:allofterms([email protected], "The Princess Bride")) {
starring {
performance.actor {
roles as count(actor.film)
}
}
}
totalRoles(func: uid(roles), orderasc: val(roles)) {
[email protected]
numRoles : val(roles)
}
}curl localhost:8080/query -XPOST -d '
{
var(func:allofterms([email protected], "The Princess Bride")) {
starring {
performance.actor {
roles as count(actor.film)
}
}
}
totalRoles(func: uid(roles), orderasc: val(roles)) {
[email protected]
numRoles : val(roles)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Variable Propagation
Like query variables, value variables can be used in other query blocks and in blocks nested within the defining block. When used in a block nested within the block that defines the variable, the value is computed as a sum of the variable for parent nodes along all paths to the point of use. This is called variable propagation.
For example:
{
q(func: uid(0x01)) {
myscore as math(1) # A
friends { # B
friends { # C
...myscore...
}
}
}
}
At line A, a value variable myscore is defined as mapping node with UID 0x01 to value 1. At B, the value for each friend is still 1: there is only one path to each friend. Traversing the friend edge twice reaches the friends of friends. The variable myscore gets propagated such that each friend of friend will receive the sum of its parents values: if a friend of a friend is reachable from only one friend, the value is still 1, if they are reachable from two friends, the value is two and so on. That is, the value of myscore for each friend of friends inside the block marked C will be the number of paths to them.
The value that a node receives for a propagated variable is the sum of the values of all its parent nodes.
This propagation is useful, for example, in normalizing a sum across users, finding the number of paths between nodes and accumulating a sum through a graph.
Query Example: For each Harry Potter movie, the number of roles played by actor Warwick Davis.
{
num_roles(func: eq([email protected], "Warwick Davis")) @cascade @normalize {
paths as math(1) # records number of paths to each character
actor : [email protected]
actor.film {
performance.film @filter(allofterms([email protected], "Harry Potter")) {
film_name : [email protected]
characters : math(paths) # how many paths (i.e. characters) reach this film
}
}
}
}curl localhost:8080/query -XPOST -d '
{
num_roles(func: eq([email protected], "Warwick Davis")) @cascade @normalize {
paths as math(1) # records number of paths to each character
actor : [email protected]
actor.film {
performance.film @filter(allofterms([email protected], "Harry Potter")) {
film_name : [email protected]
characters : math(paths) # how many paths (i.e. characters) reach this film
}
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Query Example: Each actor who has been in a Peter Jackson movie and the fraction of Peter Jackson movies they have appeared in.
{
movie_fraction(func:eq([email protected], "Peter Jackson")) @normalize {
paths as math(1)
total_films : num_films as count(director.film)
director : [email protected]
director.film {
starring {
performance.actor {
fraction : math(paths / (num_films/paths))
actor : [email protected]
}
}
}
}
}curl localhost:8080/query -XPOST -d '
{
movie_fraction(func:eq([email protected], "Peter Jackson")) @normalize {
paths as math(1)
total_films : num_films as count(director.film)
director : [email protected]
director.film {
starring {
performance.actor {
fraction : math(paths / (num_films/paths))
actor : [email protected]
}
}
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}More examples can be found in two Dgraph blog posts about using variable propagation for recommendation engines (post 1, post 2).
Aggregation
Syntax Example: AG(val(varName))
For AG replaced with
min: select the minimum value in the value variablevarNamemax: select the maximum valuesum: sum all values in value variablevarNameavg: calculate the average of values invarName
Schema Types:
| Aggregation | Schema Types |
|---|---|
min / max |
int, float, string, dateTime, default |
sum / avg |
int, float |
Aggregation can only be applied to value variables. An index is not required (the values have already been found and stored in the value variable mapping).
An aggregation is applied at the query block enclosing the variable definition. As opposed to query variables and value variables, which are global, aggregation is computed locally. For example:
A as predicateA {
...
B as predicateB {
x as ...some value...
}
min(val(x))
}
Here, A and B are the lists of all UIDs that match these blocks. Value variable x is a mapping from UIDs in B to values. The aggregation min(val(x)), however, is computed for each UID in A. That is, it has a semantics of: for each UID in A, take the slice of x that corresponds to A’s outgoing predicateB edges and compute the aggregation for those values.
Aggregations can themselves be assigned to value variables, making a UID to aggregation map.
Min
Usage at Root
Query Example: Get the min initial release date for any Harry Potter movie.
The release date is assigned to a variable, then it is aggregated and fetched in an empty block.
{
var(func: allofterms([email protected], "Harry Potter")) {
d as initial_release_date
}
me() {
min(val(d))
}
}curl localhost:8080/query -XPOST -d '
{
var(func: allofterms([email protected], "Harry Potter")) {
d as initial_release_date
}
me() {
min(val(d))
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Usage at other levels.
Query Example: Directors called Steven and the date of release of their first movie, in ascending order of first movie.
{
stevens as var(func: allofterms([email protected], "steven")) {
director.film {
ird as initial_release_date
# ird is a value variable mapping a film UID to its release date
}
minIRD as min(val(ird))
# minIRD is a value variable mapping a director UID to their first release date
}
byIRD(func: uid(stevens), orderasc: val(minIRD)) {
[email protected]
firstRelease: val(minIRD)
}
}curl localhost:8080/query -XPOST -d '
{
stevens as var(func: allofterms([email protected], "steven")) {
director.film {
ird as initial_release_date
# ird is a value variable mapping a film UID to its release date
}
minIRD as min(val(ird))
# minIRD is a value variable mapping a director UID to their first release date
}
byIRD(func: uid(stevens), orderasc: val(minIRD)) {
[email protected]
firstRelease: val(minIRD)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Max
Usage at Root
Query Example: Get the max initial release date for any Harry Potter movie.
The release date is assigned to a variable, then it is aggregated and fetched in an empty block.
{
var(func: allofterms([email protected], "Harry Potter")) {
d as initial_release_date
}
me() {
max(val(d))
}
}curl localhost:8080/query -XPOST -d '
{
var(func: allofterms([email protected], "Harry Potter")) {
d as initial_release_date
}
me() {
max(val(d))
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Usage at other levels.
Query Example: Quentin Tarantino’s movies and date of release of the most recent movie.
{
director(func: allofterms([email protected], "Quentin Tarantino")) {
director.film {
[email protected]
x as initial_release_date
}
max(val(x))
}
}curl localhost:8080/query -XPOST -d '
{
director(func: allofterms([email protected], "Quentin Tarantino")) {
director.film {
[email protected]
x as initial_release_date
}
max(val(x))
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Sum and Avg
Usage at Root
Query Example: Get the sum and average of number of count of movies directed by people who have Steven or Tom in their name.
{
var(func: anyofterms([email protected], "Steven Tom")) {
a as count(director.film)
}
me() {
avg(val(a))
sum(val(a))
}
}curl localhost:8080/query -XPOST -d '
{
var(func: anyofterms([email protected], "Steven Tom")) {
a as count(director.film)
}
me() {
avg(val(a))
sum(val(a))
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Usage at other levels.
Query Example: Steven Spielberg’s movies, with the number of recorded genres per movie, and the total number of genres and average genres per movie.
{
director(func: eq([email protected], "Steven Spielberg")) {
[email protected]
director.film {
[email protected]
numGenres : g as count(genre)
}
totalGenres : sum(val(g))
genresPerMovie : avg(val(g))
}
}curl localhost:8080/query -XPOST -d '
{
director(func: eq([email protected], "Steven Spielberg")) {
[email protected]
director.film {
[email protected]
numGenres : g as count(genre)
}
totalGenres : sum(val(g))
genresPerMovie : avg(val(g))
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Aggregating Aggregates
Aggregations can be assigned to value variables, and so these variables can in turn be aggregated.
Query Example: For each actor in a Peter Jackson film, find the number of roles played in any movie. Sum these to find the total number of roles ever played by all actors in the movie. Then sum the lot to find the total number of roles ever played by actors who have appeared in Peter Jackson movies. Note that this demonstrates how to aggregate aggregates; the answer in this case isn’t quite precise though, because actors that have appeared in multiple Peter Jackson movies are counted more than once.
{
PJ as var(func:allofterms([email protected], "Peter Jackson")) {
director.film {
starring { # starring an actor
performance.actor {
movies as count(actor.film)
# number of roles for this actor
}
perf_total as sum(val(movies))
}
movie_total as sum(val(perf_total))
# total roles for all actors in this movie
}
gt as sum(val(movie_total))
}
PJmovies(func: uid(PJ)) {
[email protected]
director.film (orderdesc: val(movie_total), first: 5) {
[email protected]
totalRoles : val(movie_total)
}
grandTotal : val(gt)
}
}curl localhost:8080/query -XPOST -d '
{
PJ as var(func:allofterms([email protected], "Peter Jackson")) {
director.film {
starring { # starring an actor
performance.actor {
movies as count(actor.film)
# number of roles for this actor
}
perf_total as sum(val(movies))
}
movie_total as sum(val(perf_total))
# total roles for all actors in this movie
}
gt as sum(val(movie_total))
}
PJmovies(func: uid(PJ)) {
[email protected]
director.film (orderdesc: val(movie_total), first: 5) {
[email protected]
totalRoles : val(movie_total)
}
grandTotal : val(gt)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Math on value variables
Value variables can be combined using mathematical functions. For example, this could be used to associate a score which is then be used to order or perform other operations, such as might be used in building newsfeeds, simple recommendation systems and the likes.
Math statements must be enclosed within math( <exp> ) and must be stored to a value variable.
The supported operators are as follows:
| Operators | Types accepted | What it does |
|---|---|---|
+ - * / % |
int, float |
performs the corresponding operation |
min max |
All types except geo, bool (binary functions) |
selects the min/max value among the two |
< > <= >= == != |
All types except geo, bool |
Returns true or false based on the values |
floor ceil ln exp sqrt |
int, float (unary function) |
performs the corresponding operation |
since |
dateTime |
Returns the number of seconds in float from the time specified |
pow(a, b) |
int, float |
Returns a to the power b |
logbase(a,b) |
int, float |
Returns log(a) to the base b |
cond(a, b, c) |
first operand must be a boolean | selects b if a is true else c |
Query Example: Form a score for each of Steven Spielberg’s movies as the sum of number of actors, number of genres and number of countries. List the top five such movies in order of decreasing score.
{
var(func:allofterms([email protected], "steven spielberg")) {
films as director.film {
p as count(starring)
q as count(genre)
r as count(country)
score as math(p + q + r)
}
}
TopMovies(func: uid(films), orderdesc: val(score), first: 5){
[email protected]
val(score)
}
}curl localhost:8080/query -XPOST -d '
{
var(func:allofterms([email protected], "steven spielberg")) {
films as director.film {
p as count(starring)
q as count(genre)
r as count(country)
score as math(p + q + r)
}
}
TopMovies(func: uid(films), orderdesc: val(score), first: 5){
[email protected]
val(score)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Value variables and aggregations of them can be used in filters.
Query Example: Calculate a score for each Steven Spielberg movie with a condition on release date to penalize movies that are more than 10 years old, filtering on the resulting score.
{
var(func:allofterms([email protected], "steven spielberg")) {
films as director.film {
p as count(starring)
q as count(genre)
date as initial_release_date
years as math(since(date)/(365*24*60*60))
score as math(cond(years > 10, 0, ln(p)+q-ln(years)))
}
}
TopMovies(func: uid(films), orderdesc: val(score)) @filter(gt(val(score), 2)){
[email protected]
val(score)
val(date)
}
}curl localhost:8080/query -XPOST -d '
{
var(func:allofterms([email protected], "steven spielberg")) {
films as director.film {
p as count(starring)
q as count(genre)
date as initial_release_date
years as math(since(date)/(365*24*60*60))
score as math(cond(years > 10, 0, ln(p)+q-ln(years)))
}
}
TopMovies(func: uid(films), orderdesc: val(score)) @filter(gt(val(score), 2)){
[email protected]
val(score)
val(date)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Values calculated with math operations are stored to value variables and so can be aggreated.
Query Example: Compute a score for each Steven Spielberg movie and then aggregate the score.
{
steven as var(func:eq([email protected], "Steven Spielberg")) @filter(has(director.film)) {
director.film {
p as count(starring)
q as count(genre)
r as count(country)
score as math(p + q + r)
}
directorScore as sum(val(score))
}
score(func: uid(steven)){
[email protected]
val(directorScore)
}
}curl localhost:8080/query -XPOST -d '
{
steven as var(func:eq([email protected], "Steven Spielberg")) @filter(has(director.film)) {
director.film {
p as count(starring)
q as count(genre)
r as count(country)
score as math(p + q + r)
}
directorScore as sum(val(score))
}
score(func: uid(steven)){
[email protected]
val(directorScore)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}GroupBy
Syntax Examples:
q(func: ...) @groupby(predicate) { min(...) }predicate @groupby(pred) { count(uid) }`
A groupby query aggregates query results given a set of properties on which to group elements. For example, a query containing the block friend @groupby(age) { count(uid) }, finds all nodes reachable along the friend edge, partitions these into groups based on age, then counts how many nodes are in each group. The returned result is the grouped edges and the aggregations.
Inside a groupby block, only aggregations are allowed and count may only be applied to uid.
If the groupby is applied to a uid predicate, the resulting aggregations can be saved in a variable (mapping the grouped UIDs to aggregate values) and used elsewhere in the query to extract information other than the grouped or aggregated edges.
Query Example: For Steven Spielberg movies, count the number of movies in each genre and for each of those genres return the genre name and the count. The name can’t be extracted in the groupby because it is not an aggregate, but uid(a) can be used to extract the UIDs from the UID to value map and thus organize the byGenre query by genre UID.
{
var(func:allofterms([email protected], "steven spielberg")) {
director.film @groupby(genre) {
a as count(uid)
# a is a genre UID to count value variable
}
}
byGenre(func: uid(a), orderdesc: val(a)) {
[email protected]
total_movies : val(a)
}
}curl localhost:8080/query -XPOST -d '
{
var(func:allofterms([email protected], "steven spielberg")) {
director.film @groupby(genre) {
a as count(uid)
# a is a genre UID to count value variable
}
}
byGenre(func: uid(a), orderdesc: val(a)) {
[email protected]
total_movies : val(a)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Query Example: Actors from Tim Burton movies and how many roles they have played in Tim Burton movies.
{
var(func:allofterms([email protected], "Tim Burton")) {
director.film {
starring @groupby(performance.actor) {
a as count(uid)
# a is an actor UID to count value variable
}
}
}
byActor(func: uid(a), orderdesc: val(a)) {
[email protected]
val(a)
}
}curl localhost:8080/query -XPOST -d '
{
var(func:allofterms([email protected], "Tim Burton")) {
director.film {
starring @groupby(performance.actor) {
a as count(uid)
# a is an actor UID to count value variable
}
}
}
byActor(func: uid(a), orderdesc: val(a)) {
[email protected]
val(a)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Expand Predicates
Keyword _predicate_ retrieves all predicates out of nodes at the level used.
Query Example: All predicates from actor Geoffrey Rush.
{
director(func: eq([email protected], "Geoffrey Rush")) {
_predicate_
}
}curl localhost:8080/query -XPOST -d '
{
director(func: eq([email protected], "Geoffrey Rush")) {
_predicate_
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}The number of predicates from a node can be counted and be aliased.
Query Example: All predicates from actor Geoffrey Rush and the count of such predicates.
{
director(func: eq([email protected], "Geoffrey Rush")) {
num_predicates: count(_predicate_)
my_predicates: _predicate_
}
}curl localhost:8080/query -XPOST -d '
{
director(func: eq([email protected], "Geoffrey Rush")) {
num_predicates: count(_predicate_)
my_predicates: _predicate_
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Predicates can be stored in a variable and passed to expand() to expand all the predicates in the variable.
If _all_ is passed as an argument to expand(), all the predicates at that level are retrieved. More levels can be specfied in a nested fashion under expand().
If _forward_ is passed as an argument to expand(), all predicates at that level (minus any reverse predicates) are retrieved.
If _reverse_ is passed as an argument to expand(), only the reverse predicates are retrieved.
Query Example: Predicates saved to a variable and queried with expand().
{
var(func: eq([email protected], "Lost in Translation")) {
pred as _predicate_
# expand(_all_) { expand(_all_)}
}
director(func: eq([email protected], "Lost in Translation")) {
[email protected]
expand(val(pred)) {
expand(_all_)
}
}
}curl localhost:8080/query -XPOST -d '
{
var(func: eq([email protected], "Lost in Translation")) {
pred as _predicate_
# expand(_all_) { expand(_all_)}
}
director(func: eq([email protected], "Lost in Translation")) {
[email protected]
expand(val(pred)) {
expand(_all_)
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}_predicate_ returns string valued predicates as a name without language tag. If the predicate has no string without a language tag, expand() won’t expand it (see language preference). For example, above name generally doesn’t have strings without tags in the dataset, so [email protected] is required.
Cascade Directive
With the @cascade directive, nodes that don’t have all predicates specified in the query are removed. This can be useful in cases where some filter was applied or if nodes might not have all listed predicates.
Query Example: Harry Potter movies, with each actor and characters played. With @cascade, any character not played by an actor called Warwick is removed, as is any Harry Potter movie without any actors called Warwick. Without @cascade, every character is returned, but only those played by actors called Warwick also have the actor name.
{
HP(func: allofterms([email protected], "Harry Potter")) @cascade {
[email protected]
starring{
performance.character {
[email protected]
}
performance.actor @filter(allofterms([email protected], "Warwick")){
[email protected]
}
}
}
}curl localhost:8080/query -XPOST -d '
{
HP(func: allofterms([email protected], "Harry Potter")) @cascade {
[email protected]
starring{
performance.character {
[email protected]
}
performance.actor @filter(allofterms([email protected], "Warwick")){
[email protected]
}
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Normalize directive
With the @normalize directive, only aliased predicates are returned and the result is flattened to remove nesting.
Query Example: Film name, country and first two actors (by UID order) of every Steven Spielberg movie, without initial_release_date because no alias is given and flattened by @normalize
{
director(func:allofterms([email protected], "steven spielberg")) @normalize {
director: [email protected]
director.film {
film: [email protected]
initial_release_date
starring(first: 2) {
performance.actor {
actor: [email protected]
}
performance.character {
character: [email protected]
}
}
country {
country: [email protected]
}
}
}
}curl localhost:8080/query -XPOST -d '
{
director(func:allofterms([email protected], "steven spielberg")) @normalize {
director: [email protected]
director.film {
film: [email protected]
initial_release_date
starring(first: 2) {
performance.actor {
actor: [email protected]
}
performance.character {
character: [email protected]
}
}
country {
country: [email protected]
}
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Ignorereflex directive
The @ignorereflex directive forces the removal of child nodes that are reachable from themselves as a parent, through any path in the query result
Query Example: All the coactors of Rutger Hauer. Without @ignorereflex, the result would also include Rutger Hauer for every movie.
{
coactors(func: eq([email protected], "Rutger Hauer")) @ignorereflex {
actor.film {
performance.film {
starring {
performance.actor {
[email protected]
}
}
}
}
}
}curl localhost:8080/query -XPOST -d '
{
coactors(func: eq([email protected], "Rutger Hauer")) @ignorereflex {
actor.film {
performance.film {
starring {
performance.actor {
[email protected]
}
}
}
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Debug
For the purposes of debugging, you can attach a query parameter debug=true to a query. Attaching this parameter lets you retrieve the uid attribute for all the entities along with the server_latency information.
Query with debug as a query parameter
curl "http://localhost:8080/query?debug=true" -XPOST -d $'{
tbl(func: allofterms([email protected], "The Big Lebowski")) {
[email protected]
}
}' | python -m json.tool | less
Returns uid and server_latency
{
"data": {
"tbl": [
{
"uid": "0x41434",
"[email protected]": "The Big Lebowski"
},
{
"uid": "0x145834",
"[email protected]": "The Big Lebowski 2"
},
{
"uid": "0x2c8a40",
"[email protected]": "Jeffrey \"The Big\" Lebowski"
},
{
"uid": "0x3454c4",
"[email protected]": "The Big Lebowski"
}
],
"server_latency": {
"parsing": "101µs",
"processing": "802ms",
"json": "115µs",
"total": "802ms"
}
}
}
Schema
For each predicate, the schema specifies the target’s type. If a predicate p has type T, then for all subject-predicate-object triples s p o the object o is of schema type T.
On mutations, scalar types are checked and an error thrown if the value cannot be converted to the schema type.
On query, value results are returned according to the schema type of the predicate.
If a schema type isn’t specified before a mutation adds triples for a predicate, then the type is inferred from the first mutation. This type is either:
type
uid, if the first mutation for the predicate has nodes for the subject and object, orderived from the rdf type, if the object is a literal and an rdf type is present in the first mutation, or
defaulttype, otherwise.
Schema Types
Dgraph supports scalar types and the UID type.
Scalar Types
For all triples with a predicate of scalar types the object is a literal.
| Dgraph Type | Go type |
|---|---|
default |
string |
int |
int64 |
float |
float |
string |
string |
bool |
bool |
dateTime |
time.Time (RFC3339 format [Optional timezone] eg: 2006-01-02T15:04:05.999999999+10:00 or 2006-01-02T15:04:05.999999999) |
geo |
go-geom |
password |
string (encrypted) |
Dgraph supports date and time formats for dateTime scalar type only if they
are RFC 3339 compatible which is different from ISO 8601(as defined in the RDF spec). You should
convert your values to RFC 3339 format before sending them to Dgraph.
UID Type
The uid type denotes a node-node edge; internally each node is represented as a uint64 id.
| Dgraph Type | Go type |
|---|---|
uid |
uint64 |
Adding or Modifying Schema
Schema mutations add or modify schema.
Multiple scalar values can also be added for a S P by specifying the schema to be of
list type. Occupations in the example below can store a list of strings for each S P.
An index is specified with @index, with arguments to specify the tokenizer. When specifying an
index for a predicate it is mandatory to specify the type of the index. For example:
name: string @index(exact, fulltext) @count .
multiname: string @lang .
age: int @index(int) .
friend: uid @count .
dob: dateTime .
location: geo @index(geo) .
occupations: [string] @index(term) .
If no data has been stored for the predicates, a schema mutation sets up an empty schema ready to receive triples.
If data is already stored before the mutation, existing values are not checked to conform to the new schema. On query, Dgraph tries to convert existing values to the new schema types, ignoring any that fail conversion.
If data exists and new indices are specified in a schema mutation, any index not in the updated list is dropped and a new index is created for every new tokenizer specified.
Reverse edges are also computed if specified by a schema mutation.
If your predicate is a URI or has special characters, then you should wrap
it with angular brackets while doing the schema mutation. E.g. <first:name>
Upsert directive
Predicates can specify the @upsert directive if you want to do upsert operations against it.
If the @upsert directive is specified then the index key for the predicate would be checked for
conflict while committing a transaction, which would allow upserts.
This is how you specify the upsert directive for a predicate. This replaces the IgnoreIndexConflict
field which was part of the mutation object in previous releases.
email: string @index(exact) @upsert .
RDF Types
Dgraph supports a number of RDF types in mutations.
As well as implying a schema type for a first mutation, an RDF type can override a schema type for storage.
If a predicate has a schema type and a mutation has an RDF type with a different underlying Dgraph type, the convertibility to schema type is checked, and an error is thrown if they are incompatible, but the value is stored in the RDF type’s corresponding Dgraph type. Query results are always returned in schema type.
For example, if no schema is set for the age predicate. Given the mutation
{
set {
_:a <age> "15"^^<xs:int> .
_:b <age> "13" .
_:c <age> "14"^^<xs:string> .
_:d <age> "14.5"^^<xs:string> .
_:e <age> "14.5" .
}
}
Dgraph:
- sets the schema type to
int, as implied by the first triple, - converts
"13"tointon storage, - checks
"14"can be converted toint, but stores asstring, - throws an error for the remaining two triples, because
"14.5"can’t be converted toint.
Extended Types
The following types are also accepted.
Password type
A password for an entity is set with setting the schema for the attribute to be of type password. Passwords cannot be queried directly, only checked for a match using the checkpwd function.
For example: to set a password, first set schema, then the password:
pass: password .
{
set {
<0x123> <name> "Password Example"
<0x123> <pass> "ThePassword" .
}
}
to check a password:
{
check(func: uid(0x123)) {
name
checkpwd(pass, "ThePassword")
}
}
output:
{
"check": [
{
"name": "Password Example",
"pass": [
{
"checkpwd": true
}
]
}
]
}
Indexing
When filtering by applying a function, Dgraph uses the index to make the search through a potentially large dataset efficient.
All scalar types can be indexed.
Types int, float, bool and geo have only a default index each: with tokenizers named int, float, bool and geo.
Types string and dateTime have a number of indices.
String Indices
The indices available for strings are as follows.
| Dgraph function | Required index / tokenizer | Notes |
|---|---|---|
eq |
hash, exact, term, or fulltext |
The most performant index for eq is hash. Only use term or fulltext if you also require term or full text search. If you’re already using term, there is no need to use hash or exact as well. |
le, ge, lt, gt |
exact |
Allows faster sorting. |
allofterms, anyofterms |
term |
Allows searching by a term in a sentence. |
alloftext, anyoftext |
fulltext |
Matching with language specific stemming and stopwords. |
regexp |
trigram |
Regular expression matching. Can also be used for equality checking. |
Incorrect index choice can impose performance penalties and an increased transaction conflict rate. Use only the minimum number of and simplest indexes that your application needs.
DateTime Indices
The indices available for dateTime are as follows.
| Index name / Tokenizer | Part of date indexed |
|---|---|
year |
index on year (default) |
month |
index on year and month |
day |
index on year, month and day |
hour |
index on year, month, day and hour |
The choices of dateTime index allow selecting the precision of the index. Applications, such as the movies examples in these docs, that require searching over dates but have relatively few nodes per year may prefer the year tokenizer; applications that are dependent on fine grained date searches, such as real-time sensor readings, may prefer the hour index.
All the dateTime indices are sortable.
Sortable Indices
Not all the indices establish a total order among the values that they index. Sortable indices allow inequality functions and sorting.
- Indexes
intandfloatare sortable. stringindexexactis sortable.- All
dateTimeindices are sortable.
For example, given an edge name of string type, to sort by name or perform inequality filtering on names, the exact index must have been specified. In which case a schema query would return at least the following tokenizers.
{
"predicate": "name",
"type": "string",
"index": true,
"tokenizer": [
"exact"
]
}
Count index
For predicates with the @count Dgraph indexes the number of edges out of each node. This enables fast queries of the form:
{
q(func: gt(count(pred), threshold)) {
...
}
}
List Type
Predicate with scalar types can also store a list of values if specified in the schema. The scalar
type needs to be enclosed within [] to indicate that its a list type. These lists are like an
unordered set.
occupations: [string] .
score: [int] .
- A set operation adds to the list of values. The order of the stored values is non-deterministic.
- A delete operation deletes the value from the list.
- Querying for these predicates would return the list in an array.
- Indexes can be applied on predicates which have a list type and you can use Functions on them.
- Sorting is not allowed using these predicates.
Reverse Edges
A graph edge is unidirectional. For node-node edges, sometimes modeling requires reverse edges. If only some subject-predicate-object triples have a reverse, these must be manually added. But if a predicate always has a reverse, Dgraph computes the reverse edges if @reverse is specified in the schema.
The reverse edge of anEdge is ~anEdge.
For existing data, Dgraph computes all reverse edges. For data added after the schema mutation, Dgraph computes and stores the reverse edge for each added triple.
Querying Schema
A schema query can query for the whole schema
schema { }
with particular schema fields
schema {
type
index
reverse
tokenizer
list
count
upsert
lang
}
and for particular predicates
schema(pred: [name, friend]) {
type
index
reverse
tokenizer
list
count
upsert
lang
}
Facets : Edge attributes
Dgraph supports facets — key value pairs on edges — as an extension to RDF triples. That is, facets add properties to edges, rather than to nodes.
For example, a friend edge between two nodes may have a boolean property of close friendship.
Facets can also be used as weights for edges.
Though you may find yourself leaning towards facets many times, they should not be misused. It wouldn’t be correct modeling to give the friend edge a facet date_of_birth. That should be an edge for the friend. However, a facet like start_of_friendship might be appropriate. Facets are however not first class citizen in Dgraph like predicates.
Facet keys are strings and values can be string, bool, int, float and dateTime.
For int and float, only decimal integers upto 32 signed bits, and 64 bit float values are accepted respectively.
The following mutation is used throughout this section on facets. The mutation adds data for some peoples and, for example, records a since facet in mobile and car to record when Alice bought the car and started using the mobile number.
First we add some schema.
curl localhost:8080/alter -XPOST -d $'
name: string @index(exact, term) .
rated: uid @reverse @count .
' | python -m json.tool | less
curl localhost:8080/mutate -H "X-Dgraph-CommitNow: true" -XPOST -d $'
{
set {
# -- Facets on scalar predicates
_:alice <name> "Alice" .
_:alice <mobile> "040123456" (since=2006-01-02T15:04:05) .
_:alice <car> "MA0123" (since=2006-02-02T13:01:09, first=true) .
_:bob <name> "Bob" .
_:bob <car> "MA0134" (since=2006-02-02T13:01:09) .
_:charlie <name> "Charlie" .
_:dave <name> "Dave" .
# -- Facets on UID predicates
_:alice <friend> _:bob (close=true, relative=false) .
_:alice <friend> _:charlie (close=false, relative=true) .
_:alice <friend> _:dave (close=true, relative=true) .
# -- Facets for variable propagation
_:movie1 <name> "Movie 1" .
_:movie2 <name> "Movie 2" .
_:movie3 <name> "Movie 3" .
_:alice <rated> _:movie1 (rating=3) .
_:alice <rated> _:movie2 (rating=2) .
_:alice <rated> _:movie3 (rating=5) .
_:bob <rated> _:movie1 (rating=5) .
_:bob <rated> _:movie2 (rating=5) .
_:bob <rated> _:movie3 (rating=5) .
_:charlie <rated> _:movie1 (rating=2) .
_:charlie <rated> _:movie2 (rating=5) .
_:charlie <rated> _:movie3 (rating=1) .
}
}' | python -m json.tool | less
Facets on scalar predicates
Querying name, mobile and car of Alice gives the same result as without facets.
{
data(func: eq(name, "Alice")) {
name
mobile
car
}
}curl localhost:8080/query -XPOST -d '
{
data(func: eq(name, "Alice")) {
name
mobile
car
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}The syntax @facets(facet-name) is used to query facet data. For Alice the since facet for mobile and car are queried as follows.
{
data(func: eq(name, "Alice")) {
name
mobile @facets(since)
car @facets(since)
}
}curl localhost:8080/query -XPOST -d '
{
data(func: eq(name, "Alice")) {
name
mobile @facets(since)
car @facets(since)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Facets are retuned at the same level as the corresponding edge and have keys like edge|facet.
All facets on an edge are queried with @facets.
{
data(func: eq(name, "Alice")) {
name
mobile @facets
car @facets
}
}curl localhost:8080/query -XPOST -d '
{
data(func: eq(name, "Alice")) {
name
mobile @facets
car @facets
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Alias with facets
Alias can be specified while requesting specific predicates. Syntax is similar to how would request
alias for other predicates. orderasc and orderdesc are not allowed as alias as they have special
meaning. Apart from that anything else can be set as alias.
Here we set car_since, close_friend alias for since, close facets respectively.
{
data(func: eq(name, "Alice")) {
name
mobile
car @facets(car_since: since)
friend @facets(close_friend: close) {
name
}
}
}curl localhost:8080/query -XPOST -d '
{
data(func: eq(name, "Alice")) {
name
mobile
car @facets(car_since: since)
friend @facets(close_friend: close) {
name
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Facets on UID predicates
Facets on UID edges work similarly to facets on value edges.
For example, friend is an edge with facet close.
It was set to true for friendship between Alice and Bob
and false for friendship between Alice and Charlie.
A query for friends of Alice.
{
data(func: eq(name, "Alice")) {
name
friend {
name
}
}
}curl localhost:8080/query -XPOST -d '
{
data(func: eq(name, "Alice")) {
name
friend {
name
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}A query for friends and the facet close with @facets(close).
{
data(func: eq(name, "Alice")) {
name
friend @facets(close) {
name
}
}
}curl localhost:8080/query -XPOST -d '
{
data(func: eq(name, "Alice")) {
name
friend @facets(close) {
name
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}For uid edges like friend, facets go to the corresponding child under the key edge|facet. In the above
example you can see that the close facet on the edge between Alice and Bob appears with the key friend|close
along with Bob’s results.
{
data(func: eq(name, "Alice")) {
name
friend @facets {
name
car @facets
}
}
}curl localhost:8080/query -XPOST -d '
{
data(func: eq(name, "Alice")) {
name
friend @facets {
name
car @facets
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Bob has a car and it has a facet since, which, in the results, is part of the same object as Bob
under the key car|since.
Also, the close relationship between Bob and Alice is part of Bob’s output object.
Charlie does not have car edge and thus only UID facets.
Filtering on facets
Dgraph supports filtering edges based on facets. Filtering works similarly to how it works on edges without facets and has the same available functions.
Find Alice’s close friends
{
data(func: eq(name, "Alice")) {
friend @facets(eq(close, true)) {
name
}
}
}curl localhost:8080/query -XPOST -d '
{
data(func: eq(name, "Alice")) {
friend @facets(eq(close, true)) {
name
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}To return facets as well as filter, add another @facets(<facetname>) to the query.
{
data(func: eq(name, "Alice")) {
friend @facets(eq(close, true)) @facets(relative) { # filter close friends and give relative status
name
}
}
}curl localhost:8080/query -XPOST -d '
{
data(func: eq(name, "Alice")) {
friend @facets(eq(close, true)) @facets(relative) { # filter close friends and give relative status
name
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Facet queries can be composed with AND, OR and NOT.
{
data(func: eq(name, "Alice")) {
friend @facets(eq(close, true) AND eq(relative, true)) @facets(relative) { # filter close friends in my relation
name
}
}
}curl localhost:8080/query -XPOST -d '
{
data(func: eq(name, "Alice")) {
friend @facets(eq(close, true) AND eq(relative, true)) @facets(relative) { # filter close friends in my relation
name
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Sorting using facets
Sorting is possible for a facet on a uid edge. Here we sort the movies rated by Alice, Bob and
Charlie by their rating which is a facet.
{
me(func: anyofterms(name, "Alice Bob Charlie")) {
name
rated @facets(orderdesc: rating) {
name
}
}
}curl localhost:8080/query -XPOST -d '
{
me(func: anyofterms(name, "Alice Bob Charlie")) {
name
rated @facets(orderdesc: rating) {
name
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Assigning Facet values to a variable
Facets on UID edges can be stored in value variables. The variable is a map from the edge target to the facet value.
Alice’s friends reported by variables for close and relative.
{
var(func: eq(name, "Alice")) {
friend @facets(a as close, b as relative)
}
friend(func: uid(a)) {
name
val(a)
}
relative(func: uid(b)) {
name
val(b)
}
}curl localhost:8080/query -XPOST -d '
{
var(func: eq(name, "Alice")) {
friend @facets(a as close, b as relative)
}
friend(func: uid(a)) {
name
val(a)
}
relative(func: uid(b)) {
name
val(b)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Facets and Variable Propagation
Facet values of int and float can be assigned to variables and thus the values propagate.
Alice, Bob and Charlie each rated every movie. A value variable on facet rating maps movies to ratings. A query that reaches a movie through multiple paths sums the ratings on each path. The following sums Alice, Bob and Charlie’s ratings for the three movies.
{
var(func: anyofterms(name, "Alice Bob Charlie")) {
num_raters as math(1)
rated @facets(r as rating) {
total_rating as math(r) # sum of the 3 ratings
average_rating as math(total_rating / num_raters)
}
}
data(func: uid(total_rating)) {
name
val(total_rating)
val(average_rating)
}
}curl localhost:8080/query -XPOST -d '
{
var(func: anyofterms(name, "Alice Bob Charlie")) {
num_raters as math(1)
rated @facets(r as rating) {
total_rating as math(r) # sum of the 3 ratings
average_rating as math(total_rating / num_raters)
}
}
data(func: uid(total_rating)) {
name
val(total_rating)
val(average_rating)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Facets and Aggregation
Facet values assigned to value variables can be aggregated.
{
data(func: eq(name, "Alice")) {
name
rated @facets(r as rating) {
name
}
avg(val(r))
}
}curl localhost:8080/query -XPOST -d '
{
data(func: eq(name, "Alice")) {
name
rated @facets(r as rating) {
name
}
avg(val(r))
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Note though that r is a map from movies to the sum of ratings on edges in the query reaching the movie. Hence, the following does not correctly calculate the average ratings for Alice and Bob individually — it calculates 2 times the average of both Alice and Bob’s ratings.
{
data(func: anyofterms(name, "Alice Bob")) {
name
rated @facets(r as rating) {
name
}
avg(val(r))
}
}curl localhost:8080/query -XPOST -d '
{
data(func: anyofterms(name, "Alice Bob")) {
name
rated @facets(r as rating) {
name
}
avg(val(r))
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}Calculating the average ratings of users requires a variable that maps users to the sum of their ratings.
{
var(func: has(~rated)) {
num_rated as math(1)
~rated @facets(r as rating) {
avg_rating as math(r / num_rated)
}
}
data(func: uid(avg_rating)) {
name
val(avg_rating)
}
}curl localhost:8080/query -XPOST -d '
{
var(func: has(~rated)) {
num_rated as math(1)
~rated @facets(r as rating) {
avg_rating as math(r / num_rated)
}
}
data(func: uid(avg_rating)) {
name
val(avg_rating)
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}K-Shortest Path Queries
The shortest path between a source (from) node and destination (to) node can be found using the keyword shortest for the query block name. It requires the source node UID, destination node UID and the predicates (atleast one) that have to be considered for traversal. A shortest query block does not return any results and requires the path has to be stored in a variable which is used in other query blocks.
By default the shortest path is returned, with numpaths: k, the k-shortest paths are returned.
shortest block, no path can be fetched as no edge is traversed.
For example:
curl localhost:8080/alter -XPOST -d $'
name: string @index(exact) .
' | python -m json.tool | less
curl localhost:8080/mutate -H "X-Dgraph-CommitNow: true" -XPOST -d $'
{
set {
_:a <friend> _:b (weight=0.1) .
_:b <friend> _:c (weight=0.2) .
_:c <friend> _:d (weight=0.3) .
_:a <friend> _:d (weight=1) .
_:a <name> "Alice" .
_:b <name> "Bob" .
_:c <name> "Tom" .
_:d <name> "Mallory" .
}
}' | python -m json.tool | less
The shortest path between Alice and Mallory (assuming UIDs 0x2 and 0x5 respectively) can be found with query:
curl localhost:8080/query -XPOST -d $'{
path as shortest(from: 0x2, to: 0x5) {
friend
}
path(func: uid(path)) {
name
}
}' | python -m json.tool | less
Which returns the following results. (Note, without considering the weight facet, each edges’ weight is considered as 1)
{
"data": {
"path": [
{
"name": "Alice"
},
{
"name": "Mallory"
}
],
"_path_": [
{
"uid": "0x2",
"friend": [
{
"uid": "0x5"
}
]
}
]
}
}
The shortest two paths are returned with:
curl localhost:8080/query -XPOST -d $'{
path as shortest(from: 0x2, to: 0x5, numpaths: 2) {
friend
}
path(func: uid(path)) {
name
}
}' | python -m json.tool | less
Edges weights are included by using facets on the edges as follows.
curl localhost:8080/query -XPOST -d $'{
path as shortest(from: 0x2, to: 0x5) {
friend @facets(weight)
}
path(func: uid(path)) {
name
}
}' | python -m json.tool | less
{
"data": {
"path": [
{
"name": "Alice"
},
{
"name": "Bob"
},
{
"name": "Tom"
},
{
"name": "Mallory"
}
],
"_path_": [
{
"uid": "0x2",
"friend": [
{
"uid": "0x3",
"friend|weight": 0.1,
"friend": [
{
"uid": "0x4",
"friend|weight": 0.2,
"friend": [
{
"uid": "0x5",
"friend|weight": 0.3
}
]
}
]
}
]
}
]
}
}
Constraints can be applied to the intermediate nodes as follows.
curl localhost:8080/query -XPOST -d $'{
path as shortest(from: 0x2, to: 0x5) {
friend @filter(not eq(name, "Bob")) @facets(weight)
relative @facets(liking)
}
relationship(func: uid(path)) {
name
}
}' | python -m json.tool | less
Recurse Query
Recurse queries let you traverse a set of predicates (with filter, facets, etc.) until we reach all leaf nodes or we reach the maximum depth which is specified by the depth parameter.
To get 10 movies from a genre that has more than 30000 films and then get two actors for those movies we’d do something as follows:
{
me(func: gt(count(~genre), 30000), first: 1) @recurse(depth: 5, loop: true) {
[email protected]
~genre (first:10) @filter(gt(count(starring), 2))
starring (first: 2)
performance.actor
}
}curl localhost:8080/query -XPOST -d '
{
me(func: gt(count(~genre), 30000), first: 1) @recurse(depth: 5, loop: true) {
[email protected]
~genre (first:10) @filter(gt(count(starring), 2))
starring (first: 2)
performance.actor
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().Query(context.Background(), `blahblah`)
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}- You can specify only one level of predicates after root. These would be traversed recursively. Both scalar and entity-nodes are treated similarly.
- Only one recurse block is advised per query.
- Be careful as the result size could explode quickly and an error would be returned if the result set gets too large. In such cases use more filters, limit results using pagination, or provide a depth parameter at root as shown in the example above.
- Loop parameter can be set to false, in which case paths which lead to a loops would be ignored while traversing.
Fragments
fragment keyword allows you to define new fragments that can be referenced in a query, as per GraphQL specification. The point is that if there are multiple parts which query the same set of fields, you can define a fragment and refer to it multiple times instead. Fragments can be nested inside fragments, but no cycles are allowed. Here is one contrived example.
curl localhost:8080/query -XPOST -d $'
query {
debug(func: uid(1)) {
[email protected]
...TestFrag
}
}
fragment TestFrag {
initial_release_date
...TestFragB
}
fragment TestFragB {
country
}' | python -m json.tool | less
GraphQL Variables
Variables can be defined and used in queries which helps in query reuse and avoids costly string building in clients at runtime by passing a separate variable map. A variable starts with a $ symbol.
query test($a: int, $b: int, $name: string) {
me(func: allofterms([email protected], $name)) {
[email protected]
director.film (first: $a, offset: $b) {
name @en
genre(first: $a) {
[email protected]
}
}
}
}curl localhost:8080/query -XPOST -H 'X-Dgraph-Vars: {"$a": "5", "$b": "10", "$name": "Steven Spielberg"}' -d '
query test($a: int, $b: int, $name: string) {
me(func: allofterms([email protected], $name)) {
[email protected]
director.film (first: $a, offset: $b) {
name @en
genre(first: $a) {
[email protected]
}
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().QueryWithVars(context.Background(), `blahblah`, map[string]string{"$a": "5", "$b": "10", "$name": "Steven Spielberg"})
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}- Variables can have default values. In the example below,
$ahas a default value of2. Since the value for$aisn’t provided in the variable map,$atakes on the default value. - Variables whose type is suffixed with a
!can’t have a default value but must have a value as part of the variables map. - The value of the variable must be parsable to the given type, if not, an error is thrown.
- The variable types that are supported as of now are:
int,float,boolandstring. - Any variable that is being used must be declared in the named query clause in the beginning.
query test($a: int = 2, $b: int!, $name: string) {
me(func: allofterms([email protected], $name)) {
director.film (first: $a, offset: $b) {
genre(first: $a) {
[email protected]
}
}
}
}curl localhost:8080/query -XPOST -H 'X-Dgraph-Vars: {"$b": "10", "$name": "Steven Spielberg"}' -d '
query test($a: int = 2, $b: int!, $name: string) {
me(func: allofterms([email protected], $name)) {
director.film (first: $a, offset: $b) {
genre(first: $a) {
[email protected]
}
}
}
}' | python -m json.tool | less
package main
import (
"context"
"flag"
"fmt"
"log"
"github.com/dgraph-io/dgo"
"github.com/dgraph-io/dgo/protos/api"
"google.golang.org/grpc"
)
var (
dgraph = flag.String("d", "127.0.0.1:9080", "Dgraph server address")
)
func main() {
flag.Parse()
conn, err := grpc.Dial(*dgraph, grpc.WithInsecure())
if err != nil {
log.Fatal(err)
}
defer conn.Close()
dg := dgo.NewDgraphClient(api.NewDgraphClient(conn))
resp, err := dg.NewTxn().QueryWithVars(context.Background(), `blahblah`, map[string]string{"$b": "10", "$name": "Steven Spielberg"})
if err != nil {
log.Fatal(err)
}
fmt.Printf("Response: %s\n", resp.Json)
}If you want to input a list of uids as a GraphQL variable value, you can have the variable as string type and
have the value surrounded by square brackets like ["13", "14"].
Indexing with Custom Tokenizers
Dgraph comes with a large toolkit of builtin indexes, but sometimes for niche use cases they’re not always enough.
Dgraph allows you to implement custom tokenizers via a plugin system in order to fill the gaps.
Caveats
The plugin system uses Go’s pkg/plugin.
This brings some restrictions to how plugins can be used.
Plugins must be written in Go.
As of Go 1.9,
pkg/pluginonly works on Linux. Therefore, plugins will only work on dgraph instances deployed in a Linux environment.The version of Go used to compile the plugin should be the same as the version of Go used to compile Dgraph itself. Dgraph always uses the latest version of Go (and so should you!).
Implementing a plugin
You should consider Go’s plugin documentation to be supplementary to the documentation provided here.
Plugins are implemented as their own main package. They must export a particular symbol that allows Dgraph to hook into the custom logic the plugin provides.
The plugin must export a symbol named Tokenizer. The type of the symbol must
be func() interface{}. When the function is called the result returned should
be a value that implements the following interface:
type PluginTokenizer interface {
// Name is the name of the tokenizer. It should be unique among all
// builtin tokenizers and other custom tokenizers. It identifies the
// tokenizer when an index is set in the schema and when search/filter
// is used in queries.
Name() string
// Identifier is a byte that uniquely identifiers the tokenizer.
// Bytes in the range 0x80 to 0xff (inclusive) are reserved for
// custom tokenizers.
Identifier() byte
// Type is a string representing the type of data that is to be
// tokenized. This must match the schema type of the predicate
// being indexde. Allowable values are shown in the table below.
Type() string
// Tokens should implement the tokenization logic. The input is
// the value to be tokenized, and will always have a concrete type
// corresponding to Type(). The return value should be a list of
// the tokens generated.
Tokens(interface{}) ([]string, error)
}
The return value of Type() corresponds to the concrete input type of
Tokens(interface{}) in the following way:
Type() return value |
Tokens(interface{}) input type |
|---|---|
"int" |
int64 |
"float" |
float64 |
"string" |
string |
"bool" |
bool |
"datetime" |
time.Time |
Building the plugin
The plugin has to be built using the plugin build mode so that an .so file
is produced instead of a regular executable. For example:
go build -buildmode=plugin -o myplugin.so ~/go/src/myplugin/main.go
Running Dgraph with plugins
When starting Dgraph, use the --custom_tokenizers flag to tell dgraph which
tokenizers to load. It accepts a comma separated list of plugins. E.g.
dgraph ...other-args... --custom_tokenizers=plugin1.so,plugin2.so
Plugin validation is performed on startup. If a problem is detected, Dgraph will refuse to initialise.
Adding the index to the schema
To use a tokenization plugin, an index has to be created in the schema.
The syntax is the same as adding any built-in index. To add an custom index
using a tokenizer plugin named foo to a string predicate named
my_predicate, use the following in the schema:
my_predicate: string @index(foo) .
Using the index in queries
There are two functions that can use custom indexes:
| Mode | Behaviour |
|---|---|
anyof |
Returns nodes that match on any of the tokens generated |
allof |
Returns nodes that match on all of the tokens generated |
The functions can be used either at the query root or in filters.
There behaviour here an analogous to anyofterms/allofterms and
anyoftext/alloftext.
Examples
The following examples should make the process of writing a tokenization plugin more concrete.
Unicode Characters
This example shows the type of tokenization that is similar to term tokenization of full text search. Instead of being broken down into terms or stem words, the text is instead broken down into its constituent unicode codepoints (in Go terminology these are called runes).
This tokenizer would create a very large index that would be expensive to manage and store. That’s one of the reasons that text indexing usually occurs at a higher level; stem words for full text search or terms for term search.
The implementation of the plugin looks like this:
package main
import "encoding/binary"
func Tokenizer() interface{} { return RuneTokenizer{} }
type RuneTokenizer struct{}
func (RuneTokenizer) Name() string { return "rune" }
func (RuneTokenizer) Type() string { return "string" }
func (RuneTokenizer) Identifier() byte { return 0xfd }
func (t RuneTokenizer) Tokens(value interface{}) ([]string, error) {
var toks []string
for _, r := range value.(string) {
var buf [binary.MaxVarintLen32]byte
n := binary.PutVarint(buf[:], int64(r))
tok := string(buf[:n])
toks = append(toks, tok)
}
return toks, nil
}
Hints and tips:
Inside
Tokens, you can assume thatvaluewill have concrete type corresponding to that specified byType(). It’s safe to do a type assertion.Even though the return value is
[]string, you can always store non-unicode data inside the string. See this blogpost for some interesting background how string are implemented in Go and why they can be used to store non-textual data. By storing arbitrary data in the string, you can make the index more compact. In this case, varints are stored in the return values.
Setting up the indexing and adding data:
name: string @index(rune) .
{
set{
_:ad <name> "Adam" .
_:aa <name> "Aaron" .
_:am <name> "Amy" .
_:ro <name> "Ronald" .
}
}
Now queries can be performed.
The only person that has all of the runes A and n in their name is Aaron:
{
q(func: allof(name, rune, "An")) {
name
}
}
=>
{
"data": {
"q": [
{ "name": "Aaron" }
]
}
}
But there are multiple people who have both of the runes A and m:
{
q(func: allof(name, rune, "Am")) {
name
}
}
=>
{
"data": {
"q": [
{ "name": "Amy" },
{ "name": "Adam" }
]
}
}
Case is taken into account, so if you search for all names containing "ron",
you would find "Aaron", but not "Ronald". But if you were to search for
"no", you would match both "Aaron" and "Ronald". The order of the runes in
the strings doesn’t matter.
It’s possible to search for people that have any of the supplied runes in
their names (rather than all of the supplied runes). To do this, use anyof
instead of allof:
{
q(func: anyof(name, rune, "mr")) {
name
}
}
=>
{
"data": {
"q": [
{ "name": "Adam" },
{ "name": "Aaron" },
{ "name": "Amy" }
]
}
}
"Ronald" doesn’t contain m or r, so isn’t found by the search.
Understanding what’s going on under the hood can help you intuitively
understand how Tokens method should be implemented.
When Dgraph sees new edges that are to be indexed by your tokenizer, it will tokenize the value. The resultant tokens are used as keys for posting lists. The edge subject is then added to the posting list for each token.
When a query root search occurs, the search value is tokenized. The result of
the search is all of the nodes in the union or intersection of the correponding
posting lists (depending on whether anyof or allof was used).
CIDR Range
Tokenizers don’t always have to be about splitting text up into its constituent parts. This example indexes IP addresses into their CIDR ranges. This allows you to search for all IP addresses that fall into a particular CIDR range.
The plugin code is more complicated than the rune example. The input is an IP
address stored as a string, e.g. "100.55.22.11/32". The output are the CIDR
ranges that the IP address could possibly fall into. There could be up to 32
different outputs ("100.55.22.11/32" does indeed have 32 possible ranges, one
for each mask size).
package main
import "net"
func Tokenizer() interface{} { return CIDRTokenizer{} }
type CIDRTokenizer struct{}
func (CIDRTokenizer) Name() string { return "cidr" }
func (CIDRTokenizer) Type() string { return "string" }
func (CIDRTokenizer) Identifier() byte { return 0xff }
func (t CIDRTokenizer) Tokens(value interface{}) ([]string, error) {
_, ipnet, err := net.ParseCIDR(value.(string))
if err != nil {
return nil, err
}
ones, bits := ipnet.Mask.Size()
var toks []string
for i := ones; i >= 1; i-- {
m := net.CIDRMask(i, bits)
tok := net.IPNet{
IP: ipnet.IP.Mask(m),
Mask: m,
}
toks = append(toks, tok.String())
}
return toks, nil
}
An example of using the tokenizer:
Setting up the indexing and adding data:
ip: string @index(cidr) .
{
set{
_:a <ip> "100.55.22.11/32" .
_:b <ip> "100.33.81.19/32" .
_:c <ip> "100.49.21.25/32" .
_:d <ip> "101.0.0.5/32" .
_:e <ip> "100.176.2.1/32" .
}
}
{
q(func: allof(ip, cidr, "100.48.0.0/12")) {
ip
}
}
=>
{
"data": {
"q": [
{ "ip": "100.55.22.11/32" },
{ "ip": "100.49.21.25/32" }
]
}
}
The CIDR ranges of 100.55.22.11/32 and 100.49.21.25/32 are both
100.48.0.0/12. The other IP addresses in the database aren’t included in the
search result, since they have different CIDR ranges for 12 bit masks
(100.32.0.0/12, 101.0.0.0/12, 100.154.0.0/12 for 100.33.81.19/32,
101.0.0.5/32, and 100.176.2.1/32 respectively).
Note that we’re using allof instead of anyof. Only allof will work
correctly with this index. Remember that the tokenizer generates all possible
CIDR ranges for an IP address. If we were to use anyof then the search result
would include all IP addresses under the 1 bit mask (in this case, 0.0.0.0/1,
which would match all IPs in this dataset).
Anagram
Tokenizers don’t always have to return multiple tokens. If you just want to index data into groups, have the tokenizer just return an identifying member of that group.
In this example, we want to find groups of words that are anagrams of each other.
A token to correspond to a group of anagrams could just be the letters in the anagram in sorted order, as implemented below:
package main
import "sort"
func Tokenizer() interface{} { return AnagramTokenizer{} }
type AnagramTokenizer struct{}
func (AnagramTokenizer) Name() string { return "anagram" }
func (AnagramTokenizer) Type() string { return "string" }
func (AnagramTokenizer) Identifier() byte { return 0xfc }
func (t AnagramTokenizer) Tokens(value interface{}) ([]string, error) {
b := []byte(value.(string))
sort.Slice(b, func(i, j int) bool { return b[i] < b[j] })
return []string{string(b)}, nil
}
In action:
Setting up the indexing and adding data:
word: string @index(anagram) .
{
set{
_:1 <word> "airmen" .
_:2 <word> "marine" .
_:3 <word> "beat" .
_:4 <word> "beta" .
_:5 <word> "race" .
_:6 <word> "care" .
}
}
{
q(func: allof(word, anagram, "remain")) {
word
}
}
=>
{
"data": {
"q": [
{ "word": "airmen" },
{ "word": "marine" }
]
}
}
Since a single token is only ever generated, it doesn’t matter if anyof or
allof is used. The result will always be the same.
Integer prime factors
All all of the custom tokenizers shown previously have worked with strings. However, other data types can be used as well. This example is contrived, but nonetheless shows some advanced usages of custom tokenizers.
The tokenizer creates a token for each prime factor in the input.
package main
import (
"encoding/binary"
"fmt"
)
func Tokenizer() interface{} { return FactorTokenizer{} }
type FactorTokenizer struct{}
func (FactorTokenizer) Name() string { return "factor" }
func (FactorTokenizer) Type() string { return "int" }
func (FactorTokenizer) Identifier() byte { return 0xfe }
func (FactorTokenizer) Tokens(value interface{}) ([]string, error) {
x := value.(int64)
if x <= 1 {
return nil, fmt.Errorf("cannot factor int <= 1: %d", x)
}
var toks []string
for p := int64(2); x > 1; p++ {
if x%p == 0 {
toks = append(toks, encodeInt(p))
for x%p == 0 {
x /= p
}
}
}
return toks, nil
}
func encodeInt(x int64) string {
var buf [binary.MaxVarintLen64]byte
n := binary.PutVarint(buf[:], x)
return string(buf[:n])
}
Notice that the return of Type() is "int", corresponding to the concrete
type of the input to Tokens (which is int64).
This allows you do do things like search for all numbers that share prime factors with a particular number.
In particular, we search for numbers that contain any of the prime factors of 15, i.e. any numbers that are divisible by either 3 or 5.
Setting up the indexing and adding data:
num: int @index(factor) .
{
set{
_:2 <num> "2"^^<xs:int> .
_:3 <num> "3"^^<xs:int> .
_:4 <num> "4"^^<xs:int> .
_:5 <num> "5"^^<xs:int> .
_:6 <num> "6"^^<xs:int> .
_:7 <num> "7"^^<xs:int> .
_:8 <num> "8"^^<xs:int> .
_:9 <num> "9"^^<xs:int> .
_:10 <num> "10"^^<xs:int> .
_:11 <num> "11"^^<xs:int> .
_:12 <num> "12"^^<xs:int> .
_:13 <num> "13"^^<xs:int> .
_:14 <num> "14"^^<xs:int> .
_:15 <num> "15"^^<xs:int> .
_:16 <num> "16"^^<xs:int> .
_:17 <num> "17"^^<xs:int> .
_:18 <num> "18"^^<xs:int> .
_:19 <num> "19"^^<xs:int> .
_:20 <num> "20"^^<xs:int> .
_:21 <num> "21"^^<xs:int> .
_:22 <num> "22"^^<xs:int> .
_:23 <num> "23"^^<xs:int> .
_:24 <num> "24"^^<xs:int> .
_:25 <num> "25"^^<xs:int> .
_:26 <num> "26"^^<xs:int> .
_:27 <num> "27"^^<xs:int> .
_:28 <num> "28"^^<xs:int> .
_:29 <num> "29"^^<xs:int> .
_:30 <num> "30"^^<xs:int> .
}
}
{
q(func: anyof(num, factor, 15)) {
num
}
}
=>
{
"data": {
"q": [
{ "num": 3 },
{ "num": 5 },
{ "num": 6 },
{ "num": 9 },
{ "num": 10 },
{ "num": 12 },
{ "num": 15 },
{ "num": 18 }
{ "num": 20 },
{ "num": 21 },
{ "num": 25 },
{ "num": 24 },
{ "num": 27 },
{ "num": 30 },
]
}
}