Nebula Spark Connector¶
Nebula Spark Connector is a Spark connector application for reading and writing NebulaGraph data in Spark standard format. Nebula Spark Connector consists of two parts: Reader and Writer.
-
Reader
Provides a Spark SQL interface. This interface can be used to read NebulaGraph data. It reads one vertex or edge type data at a time and assemble the result into a Spark DataFrame.
-
Writer
Provides a Spark SQL interface. This interface can be used to write DataFrames into NebulaGraph in a row-by-row or batch-import way.
For more information, see Nebula Spark Connector.
Use cases¶
Nebula Spark Connector applies to the following scenarios:
- Migrate data between different NebulaGraph clusters.
- Migrate data between different graph spaces in the same NebulaGraph cluster.
- Migrate data between NebulaGraph and other data sources.
- Graph computing with Nebula Algorithm.
Benefits¶
The features of Nebula Spark Connector 3.0.0 are as follows:
- Supports multiple connection settings, such as timeout period, number of connection retries, number of execution retries, etc.
- Supports multiple settings for data writing, such as setting the corresponding column as vertex ID, starting vertex ID, destination vertex ID or attributes.
- Supports non-attribute reading and full attribute reading.
- Supports reading NebulaGraph data into VertexRDD and EdgeRDD, and supports non-Long vertex IDs.
- Unifies the extended data source of SparkSQL, and uses DataSourceV2 to extend NebulaGraph data.
- Three write modes,
insert
,update
anddelete
, are supported.insert
mode will insert (overwrite) data,update
mode will only update existing data, anddelete
mode will only delete data.
Release note¶
Get Nebula Spark Connector¶
Compile package¶
Note
Install Nebula Spark Connector of version 2.4.x.
-
Clone repository
nebula-spark-connector
.$ git clone -b v3.0.0 https://github.com/vesoft-inc/nebula-spark-connector.git
-
Make the
nebula-spark-connector
directory the current working directory.$ cd nebula-spark-connector/nebula-spark-connector
-
Compile package.
$ mvn clean package -Dmaven.test.skip=true -Dgpg.skip -Dmaven.javadoc.skip=true
After compilation, a similar file nebula-spark-connector-3.0.0-SHANPSHOT.jar
is generated in the directory nebula-spark-connector/nebula-spark-connector/target/
.
Download maven remote repository¶
How to use¶
When using Nebula Spark Connector to reading and writing NebulaGraph data, You can refer to the following code.
# Read vertex and edge data from NebulaGraph.
spark.read.nebula().loadVerticesToDF()
spark.read.nebula().loadEdgesToDF()
# Write dataframe data into NebulaGraph as vertex and edges.
dataframe.write.nebula().writeVertices()
dataframe.write.nebula().writeEdges()
nebula()
receives two configuration parameters, including connection configuration and read-write configuration.
Reading data from NebulaGraph¶
val config = NebulaConnectionConfig
.builder()
.withMetaAddress("127.0.0.1:9559")
.withConenctionRetry(2)
.withExecuteRetry(2)
.withTimeout(6000)
.build()
val nebulaReadVertexConfig: ReadNebulaConfig = ReadNebulaConfig
.builder()
.withSpace("test")
.withLabel("person")
.withNoColumn(false)
.withReturnCols(List("birthday"))
.withLimit(10)
.withPartitionNum(10)
.build()
val vertex = spark.read.nebula(config, nebulaReadVertexConfig).loadVerticesToDF()
val nebulaReadEdgeConfig: ReadNebulaConfig = ReadNebulaConfig
.builder()
.withSpace("test")
.withLabel("knows")
.withNoColumn(false)
.withReturnCols(List("degree"))
.withLimit(10)
.withPartitionNum(10)
.build()
val edge = spark.read.nebula(config, nebulaReadEdgeConfig).loadEdgesToDF()
-
NebulaConnectionConfig
is the configuration for connecting to the NebulaGraph, as described below.Parameter Required Description withMetaAddress
Yes Specifies the IP addresses and ports of all Meta Services. Separate multiple addresses with commas. The format is ip1:port1,ip2:port2,...
. Read data is no need to configurewithGraphAddress
.withConnectionRetry
No The number of retries that the Nebula Java Client connected to the NebulaGraph. The default value is 1
.withExecuteRetry
No The number of retries that the Nebula Java Client executed query statements. The default value is 1
.withTimeout
No The timeout for the Nebula Java Client request response. The default value is 6000
, Unit: ms.
-
ReadNebulaConfig
is the configuration to read NebulaGraph data, as described below.Parameter Required Description withSpace
Yes NebulaGraph space name. withLabel
Yes The Tag or Edge type name within the NebulaGraph space. withNoColumn
No Whether the property is not read. The default value is false
, read property. If the value istrue
, the property is not read, thewithReturnCols
configuration is invalid.withReturnCols
No Configures the set of properties for vertex or edges to read. the format is List(property1,property2,...)
, The default value isList()
, indicating that all properties are read.withLimit
No Configure the number of rows of data read from the server by the Nebula Java Storage Client at a time. The default value is 1000
.withPartitionNum
No Configures the number of Spark partitions to read the NebulaGraph data. The default value is 100
. This value should not exceed the number of slices in the graph space (partition_num).
Write data into NebulaGraph¶
Note
The values of columns in a dataframe are automatically written to the NebulaGraph as property values.
val config = NebulaConnectionConfig
.builder()
.withMetaAddress("127.0.0.1:9559")
.withGraphAddress("127.0.0.1:9669")
.withConenctionRetry(2)
.build()
val nebulaWriteVertexConfig: WriteNebulaVertexConfig = WriteNebulaVertexConfig
.builder()
.withSpace("test")
.withTag("person")
.withVidField("id")
.withVidPolicy("hash")
.withVidAsProp(true)
.withUser("root")
.withPasswd("nebula")
.withBatch(1000)
.build()
df.write.nebula(config, nebulaWriteVertexConfig).writeVertices()
val nebulaWriteEdgeConfig: WriteNebulaEdgeConfig = WriteNebulaEdgeConfig
.builder()
.withSpace("test")
.withEdge("friend")
.withSrcIdField("src")
.withSrcPolicy(null)
.withDstIdField("dst")
.withDstPolicy(null)
.withRankField("degree")
.withSrcAsProperty(true)
.withDstAsProperty(true)
.withRankAsProperty(true)
.withUser("root")
.withPasswd("nebula")
.withBatch(1000)
.build()
df.write.nebula(config, nebulaWriteEdgeConfig).writeEdges()
The default write mode is insert
, which can be changed to update
via withWriteMode
configuration:
val config = NebulaConnectionConfig
.builder()
.withMetaAddress("127.0.0.1:9559")
.withGraphAddress("127.0.0.1:9669")
.build()
val nebulaWriteVertexConfig = WriteNebulaVertexConfig
.builder()
.withSpace("test")
.withTag("person")
.withVidField("id")
.withVidAsProp(true)
.withBatch(1000)
.withWriteMode(WriteMode.UPDATE)
.build()
df.write.nebula(config, nebulaWriteVertexConfig).writeVertices()
-
NebulaConnectionConfig
is the configuration for connecting to the NebulaGraph, as described below.Parameter Required Description withMetaAddress
Yes Specifies the IP addresses and ports of all Meta Services. Separate multiple addresses with commas. The format is ip1:port1,ip2:port2,...
.withGraphAddress
Yes Specifies the IP addresses and ports of Graph Services. Separate multiple addresses with commas. The format is ip1:port1,ip2:port2,...
.withConnectionRetry
No Number of retries that the Nebula Java Client connected to the NebulaGraph. The default value is 1
.
-
WriteNebulaVertexConfig
is the configuration of the write vertex, as described below.Parameter Required Description withSpace
Yes NebulaGraph space name. withTag
Yes The Tag name that needs to be associated when a vertex is written. withVidField
Yes The column in the DataFrame as the vertex ID. withVidPolicy
No When writing the vertex ID, NebulaGraph use mapping function, supports HASH only. No mapping is performed by default. withVidAsProp
No Whether the column in the DataFrame that is the vertex ID is also written as an property. The default value is false
. If set totrue
, make sure the Tag has the same property name asVidField
.withUser
No NebulaGraph user name. If authentication is disabled, you do not need to configure the user name and password. withPasswd
No The password for the NebulaGraph user name. withBatch
Yes The number of rows of data written at a time. The default value is 1000
.withWriteMode
No Write mode. The optional values are insert
andupdate
. The default value isinsert
.
-
WriteNebulaEdgeConfig
is the configuration of the write edge, as described below.Parameter Required Description withSpace
Yes NebulaGraph space name. withEdge
Yes The Edge type name that needs to be associated when a edge is written. withSrcIdField
Yes The column in the DataFrame as the vertex ID. withSrcPolicy
No When writing the starting vertex ID, NebulaGraph use mapping function, supports HASH only. No mapping is performed by default. withDstIdField
Yes The column in the DataFrame that serves as the destination vertex. withDstPolicy
No When writing the destination vertex ID, NebulaGraph use mapping function, supports HASH only. No mapping is performed by default. withRankField
No The column in the DataFrame as the rank. Rank is not written by default. withSrcAsProperty
No Whether the column in the DataFrame that is the starting vertex is also written as an property. The default value is false
. If set totrue
, make sure Edge type has the same property name asSrcIdField
.withDstAsProperty
No Whether column that are destination vertex in the DataFrame are also written as property. The default value is false
. If set totrue
, make sure Edge type has the same property name asDstIdField
.withRankAsProperty
No Whether column in the DataFrame that is the rank is also written as property.The default value is false
. If set totrue
, make sure Edge type has the same property name asRankField
.withUser
No NebulaGraph user name. If authentication is disabled, you do not need to configure the user name and password. withPasswd
No The password for the NebulaGraph user name. withBatch
Yes The number of rows of data written at a time. The default value is 1000
.withWriteMode
No Write mode. The optional values are insert
andupdate
. The default value isinsert
.