DataStax Enterprise Node.js Driver
This driver is built on top of Node.js CQL driver for Apache Cassandra and provides the following
additions for DataStax Enterprise:
Authenticator
implementations that use the authentication scheme negotiation in the server-side DseAuthenticator
;- encoders for geospatial types which integrate seamlessly with the driver;
- DSE graph integration.
The DataStax Enterprise Node.js Driver can be used solely with DataStax Enterprise. Please consult
the license.
Installation
npm install dse-driver
Documentation
Getting Help
You can use the project mailing list or create a ticket on the Jira issue tracker.
Getting Started
Client
inherits from the CQL driver counterpart Client
. All CQL features available to Client
(see the
CQL driver manual) can also be used with Client
.
const dse = require('dse-driver');
const client = new dse.Client({ contactPoints: ['host1', 'host2'] });
const query = 'SELECT name, email FROM users WHERE key = ?';
client.execute(query, [ 'someone' ])
.then(result => console.log('User with email %s', result.rows[0].email));
Alternatively, you can use the callback-based execution for all asynchronous methods of the API.
client.execute(query, [ 'someone' ], function(err, result) {
assert.ifError(err);
console.log('User with email %s', result.rows[0].email);
});
The dse-driver
module also exports the submodules from the CQL driver, so you only need to import one module to access
all DSE and Cassandra types.
For example:
const dse = require('dse-driver');
const Uuid = dse.types.Uuid;
Authentication
For clients connecting to a DSE cluster secured with DseAuthenticator
, two authentication providers are included:
DsePlainTextAuthProvider
: Plain-text authentication;DseGSSAPIAuthProvider
: GSSAPI authentication;
To configure a provider, pass it when initializing a cluster:
const dse = require('dse-driver');
const client = new dse.Client({
contactPoints: ['h1', 'h2'],
keyspace: 'ks1',
authProvider: new dse.auth.DseGssapiAuthProvider()
});
See the jsdoc of each implementation for more details.
Graph
Client
includes the executeGraph()
method to execute graph queries:
const client = new dse.Client({
contactPoints: ['host1', 'host2'],
profiles: [
new ExecutionProfile('default', {
graphOptions: { name: 'demo' }
})
]
});
const result = await client.executeGraph('g.V()');
const vertex = result.first();
console.log(vertex.label);
Graph Options
You can set graph options in execution profiles when initializing Client
. Also, to avoid providing the graph name
option in each executeGraph()
call, you can set the graph options in the default execution profile:
const client = new dse.Client({
contactPoints: ['host1', 'host2'],
profiles: [
new ExecutionProfile('default', {
graphOptions: { name: 'demo' }
}),
new ExecutionProfile('demo2-profile', {
graphOptions: { name: 'demo2' }
})
]
});
const result = await client.executeGraph(query, params);
If needed, you can specify an execution profile different from the default one:
client.executeGraph(query, params, { executionProfile: 'demo2-profile'});
Additionally, you can also set the default graph options without using execution profiles (not recommended).
const client = new dse.Client({
contactPoints: ['host1', 'host2'],
graphOptions: { name: 'demo' }
});
Handling Results
Graph queries return a GraphResultSet
, which is an iterable of rows. The format of the data returned is
dependent on the data requested. For example, the payload representing edges will be different than those that
represent vertices using the 'modern' graph:
const query =
'Vertex marko = graph.addVertex(label, "person", "name", "marko", "age", 29);\n' +
'Vertex vadas = graph.addVertex(label, "person", "name", "vadas", "age", 27);\n' +
'Vertex lop = graph.addVertex(label, "software", "name", "lop", "lang", "java");\n' +
'Vertex josh = graph.addVertex(label, "person", "name", "josh", "age", 32);\n' +
'Vertex ripple = graph.addVertex(label, "software", "name", "ripple", "lang", "java");\n' +
'Vertex peter = graph.addVertex(label, "person", "name", "peter", "age", 35);\n' +
'marko.addEdge("knows", vadas, "weight", 0.5f);\n' +
'marko.addEdge("knows", josh, "weight", 1.0f);\n' +
'marko.addEdge("created", lop, "weight", 0.4f);\n' +
'josh.addEdge("created", ripple, "weight", 1.0f);\n' +
'josh.addEdge("created", lop, "weight", 0.4f);\n' +
'peter.addEdge("created", lop, "weight", 0.2f);';
await client.executeGraph(query);
const result = await client.executeGraph('g.E()');
result.forEach(function (edge) {
console.log(edge.id);
console.log(edge.type);
console.log(edge.label);
console.log(edge.properties.weight);
console.log(edge.outVLabel);
console.log(edge.outV);
console.log(edge.inVLabel);
console.log(edge.inV);
});
const result = await client.executeGraph('g.E()');
for (let edge of result) {
console.log(edge.label);
}
const result = await client.executeGraph('g.V().hasLabel("person")');
result.forEach(function(vertex) {
console.log(vertex.id);
console.log(vertex.type);
console.log(vertex.label);
console.log(vertex.properties.name[0].value);
console.log(vertex.properties.age[0].value);
});
Parameters
Unlike CQL queries which support both positional and named parameters, graph queries only support named parameters.
As a result of this, parameters must be passed in as an object:
const query = 'g.addV(label, vertexLabel, "name", username)';
const result = await client.executeGraph(query, { vertexLabel: 'person', username: 'marko' });
const vertex = result.first();
Parameters are encoded in json, thus will ultimately use their json representation (toJSON
if present,
otherwise object representation).
You can use results from previous queries as parameters to subsequent queries. For example, if you want to use the id
of a vertex returned in a previous query for making a subsequent query:
let result = await client.executeGraph('g.V().hasLabel("person").has("name", "marko")');
const vertex = result.first();
result = await client.executeGraph('g.V(vertexId).out("knows").values("name")', { vertexId: vertex.id });
const names = result.toArray();
console.log(names);
Prepared graph statements
Prepared graph statements are not supported by DSE Graph yet (they will be added in the near future).
Geospatial types
DSE 5.0 comes with a set of additional CQL types to represent geospatial data: PointType
, LineStringType
and
PolygonType
.
cqlsh> CREATE TABLE points_of_interest(name text PRIMARY KEY, coords 'PointType');
cqlsh> INSERT INTO points_of_interest (name, coords) VALUES ('Eiffel Tower', 'POINT(48.8582 2.2945)');
The DSE driver includes encoders and representations of these types in the geometry
module that can be used directly
as parameters in queries:
const dse = require('dse-driver');
const Point = dse.geometry.Point;
const insertQuery = 'INSERT INTO points_of_interest (name, coords) VALUES (?, ?)';
const selectQuery = 'SELECT coords FROM points_of_interest WHERE name = ?';
await client.execute(insertQuery, [ 'Eiffel Tower', new Point(48.8582, 2.2945) ], { prepare: true });
const result = await client.execute(selectQuery, ['Eiffel Tower'], { prepare: true });
const row = result.first();
const point = row['coords'];
console.log(point instanceof Point);
console.log('x: %d, y: %d', point.x, point.y);
License
Copyright 2016 DataStax
http://www.datastax.com/terms/datastax-dse-driver-license-terms