Import data from Oracle¶

This topic provides an example of how to use Exchange to export Oracle data and import to NebulaGraph.

Data set¶

This topic takes the basketballplayer dataset as an example.

In this example, the data set has been stored in Oracle. All vertexes and edges are stored in the player, team, follow, and serve tables. The following are some of the data for each table.

oracle> desc player;
+-----------+-------+---------------+ 
| Column    | Null  | Type          |
+-----------+-------+---------------+ 
| PLAYERID  |  -    | VARCHAR2(30)  |
| NAME      |  -    | VARCHAR2(30)  |
| AGE       |  -    | NUMBER        |
+-----------+-------+---------------+ 

oracle> desc team;
+-----------+-------+---------------+ 
| Column    | Null  | Type          |
+-----------+-------+---------------+ 
| TEAMID    |  -    | VARCHAR2(30)  |
| NAME      |  -    | VARCHAR2(30)  |
+-----------+-------+---------------+ 

oracle> desc follow;
+-------------+-------+---------------+ 
| Column      | Null  | Type          |
+-------------+-------+---------------+ 
| SRC_PLAYER  |  -    | VARCHAR2(30)  |
| DST_PLAYER  |  -    | VARCHAR2(30)  |
| DEGREE      |  -    | NUMBER        |
+-------------+-------+---------------+ 

oracle> desc serve;
+------------+-------+---------------+ 
| Column     | Null  | Type          |
+------------+-------+---------------+ 
| PLAYERID   |  -    | VARCHAR2(30)  |
| TEAMID     |  -    | VARCHAR2(30)  |
| START_YEAR |  -    | NUMBER        |
| END_YEAR   |  -    | NUMBER        |
+------------+-------+---------------+

Environment¶

This example is done on MacOS. Here is the environment configuration information:

Hardware specifications:
- CPU: 1.7 GHz Quad-Core Intel Core i7
- Memory: 16 GB

Spark: 2.4.7, stand-alone

NebulaGraph: 3.5.0. Deploy NebulaGraph with Docker Compose.

Prerequisites¶

Before importing data, you need to confirm the following information:

NebulaGraph has been installed and deployed with the following information:
- IP addresses and ports of Graph and Meta services.
- The user name and password with write permission to NebulaGraph.

Exchange has been compiled, or download the compiled .jar file directly.

Spark has been installed.

Learn about the Schema created in NebulaGraph, including names and properties of Tags and Edge types, and more.

The Hadoop service has been installed and started.

Precautions¶

nebula-exchange_spark_2.2 supports only single table queries, not multi-table queries.

Steps¶

Step 1: Create the Schema in NebulaGraph¶

Analyze the data to create a Schema in NebulaGraph by following these steps:

Identify the Schema elements. The Schema elements in the NebulaGraph are shown in the following table.

Element Name Property

Tag player name string, age int

Tag team name string

Edge Type follow degree int

Edge Type serve start_year int, end_year int

Create a graph space basketballplayer in the NebulaGraph and create a Schema as shown below.

## Create a graph space.
nebula> CREATE SPACE basketballplayer \
        (partition_num = 10, \
        replica_factor = 1, \
        vid_type = FIXED_STRING(30));

## Use the graph space basketballplayer.
nebula> USE basketballplayer;

## Create the Tag player.
nebula> CREATE TAG player(name string, age int);

## Create the Tag team.
nebula> CREATE TAG team(name string);

## Create the Edge type follow.
nebula> CREATE EDGE follow(degree int);

## Create the Edge type serve.
nebula> CREATE EDGE serve(start_year int, end_year int);

For more information, see Quick start workflow.

Step 2: Modify configuration files¶

After Exchange is compiled, copy the conf file target/classes/application.conf to set Oracle data source configuration. In this case, the copied file is called oracle_application.conf. For details on each configuration item, see Parameters in the configuration file.

{
  # Spark configuration
  spark: {
    app: {
      name: NebulaGraph Exchange 3.5.0
    }
    driver: {
      cores: 1
      maxResultSize: 1G
    }
    cores: {
      max: 16
    }
  }

  # NebulaGraph configuration
  nebula: {
    address:{
      # Specify the IP addresses and ports for Graph and Meta services.
      # If there are multiple addresses, the format is "ip1:port","ip2:port","ip3:port".
      # Addresses are separated by commas.
      graph:["127.0.0.1:9669"]
      # the address of any of the meta services.
      # if your NebulaGraph server is in virtual network like k8s, please config the leader address of meta.
      meta:["127.0.0.1:9559"]
    }
    # The account entered must have write permission for the NebulaGraph space.
    user: root
    pswd: nebula
    # Fill in the name of the graph space you want to write data to in the NebulaGraph.
    space: basketballplayer
    connection: {
      timeout: 3000
      retry: 3
    }
    execution: {
      retry: 3
    }
    error: {
      max: 32
      output: /tmp/errors
    }
    rate: {
      limit: 1024
      timeout: 1000
    }
  }
  # Processing vertexes
  tags: [
    # Set the information about the Tag player.
    {
      # The Tag name in NebulaGraph.
      name: player
      type: {
        # Specify the data source file format to Oracle.
        source: oracle
        # Specify how to import the data into NebulaGraph: Client or SST.
        sink: client
      }

      url:"jdbc:oracle:thin:@host:1521:basketball"
      driver: "oracle.jdbc.driver.OracleDriver"
      user: "root"
      password: "123456"

      # Scanning a single table to read data.
      # nebula-exchange_spark_2.2 must configure this parameter. Sentence is not supported.
      # nebula-exchange_spark_2.4 and nebula-exchange_spark_3.0 can configure this parameter, but not at the same time as sentence.
      table:"basketball.player"

      # Use query statement to read data.
      # This parameter is not supported by nebula-exchange_spark_2.2.
      # nebula-exchange_spark_2.4 and nebula-exchange_spark_3.0 can configure this parameter, but not at the same time as table. Multi-table queries are supported.
      # sentence: "select * from people, player, team"

      # Specify the column names in the player table in fields, and their corresponding values are specified as properties in the NebulaGraph.
      # The sequence of fields and nebula.fields must correspond to each other.
      # If multiple column names need to be specified, separate them by commas.
      fields: [age,name]
      nebula.fields: [age,name]

      # Specify a column of data in the table as the source of VIDs in the NebulaGraph.
      vertex: {
        field:playerid
      # udf:{
      #            separator:"_"
      #            oldColNames:[field-0,field-1,field-2]
      #            newColName:new-field
      #        }
      # Add the specified prefix to the VID. For example, if the VID is `12345`, adding the prefix `tag1` will result in `tag1_12345`. The underscore cannot be modified.
      # prefix:"tag1"
      # Performs hashing operations on VIDs of type string.
      # policy:hash
      }

      # Batch operation types, including INSERT, UPDATE, and DELETE. defaults to INSERT.
      #writeMode: INSERT

      # Whether or not to delete the related incoming and outgoing edges of the vertices when performing a batch delete operation. This parameter takes effect when `writeMode` is `DELETE`.
      #deleteEdge: false

      # The number of data written to NebulaGraph in a single batch.
      batch: 256

      # The number of Spark partitions.
      partition: 32
    }
    # Set the information about the Tag Team.
    {
      name: team
      type: {
        source: oracle
        sink: client
      }

      url:"jdbc:oracle:thin:@host:1521:basketball"
      driver: "oracle.jdbc.driver.OracleDriver"
      user: "root"
      password: "123456"
      table: "basketball.team"
      sentence: "select teamid, name from team"

      fields: [name]
      nebula.fields: [name]
      vertex: {
        field: teamid
      }
      batch: 256
      partition: 32
    }

  ]

  # Processing edges
  edges: [
    # Set the information about the Edge Type follow.
    {
      # The corresponding Edge Type name in NebulaGraph.
      name: follow

      type: {
        # Specify the data source file format to Oracle.
        source: oracle

        # Specify how to import the Edge type data into NebulaGraph.
        # Specify how to import the data into NebulaGraph: Client or SST.
        sink: client
      }

      url:"jdbc:oracle:thin:@host:1521:basketball"
      driver: "oracle.jdbc.driver.OracleDriver"
      user: "root"
      password: "123456"

      # Scanning a single table to read data.
      # nebula-exchange_spark_2.2 must configure this parameter. Sentence is not supported.
      # nebula-exchange_spark_2.4 and nebula-exchange_spark_3.0 can configure this parameter, but not at the same time as sentence.
      table:"basketball.follow"

      # Use query statement to read data.
      # This parameter is not supported by nebula-exchange_spark_2.2.
      # nebula-exchange_spark_2.4 and nebula-exchange_spark_3.0 can configure this parameter, but not at the same time as table. Multi-table queries are supported.
      # sentence: "select * from follow, serve"

      # Specify the column names in the follow table in fields, and their corresponding values are specified as properties in the NebulaGraph.
      # The sequence of fields and nebula.fields must correspond to each other.
      # If multiple column names need to be specified, separate them by commas.
      fields: [degree]
      nebula.fields: [degree]

      # In source, use a column in the follow table as the source of the edge's source vertex.
      # In target, use a column in the follow table as the source of the edge's destination vertex.
      source: {
        field: src_player
      # udf:{
      #            separator:"_"
      #            oldColNames:[field-0,field-1,field-2]
      #            newColName:new-field
      #        }
      # Add the specified prefix to the VID. For example, if the VID is `12345`, adding the prefix `tag1` will result in `tag1_12345`. The underscore cannot be modified.
      # prefix:"tag1"
      # Performs hashing operations on VIDs of type string.
      # policy:hash
      }

      target: {
        field: dst_player
      # udf:{
      #            separator:"_"
      #            oldColNames:[field-0,field-1,field-2]
      #            newColName:new-field
      #        }
      # Add the specified prefix to the VID. For example, if the VID is `12345`, adding the prefix `tag1` will result in `tag1_12345`. The underscore cannot be modified.
      # prefix:"tag1"
      # Performs hashing operations on VIDs of type string.
      # policy:hash
      }

      # (Optional) Specify a column as the source of the rank.
      #ranking: rank

      # Batch operation types, including INSERT, UPDATE, and DELETE. defaults to INSERT.
      #writeMode: INSERT

      # The number of data written to NebulaGraph in a single batch.
      batch: 256

      # The number of Spark partitions.
      partition: 32
    }

    # Set the information about the Edge Type serve.
    {
      name: serve
      type: {
        source: oracle
        sink: client
      }

      url:"jdbc:oracle:thin:@host:1521:basketball"
      driver: "oracle.jdbc.driver.OracleDriver"
      user: "root"
      password: "123456"
      table: "basketball.serve"
      sentence: "select playerid, teamid, start_year, end_year from serve"

      fields: [start_year,end_year]
      nebula.fields: [start_year,end_year]
      source: {
        field: playerid
      }
      target: {
        field: teamid
      }
      batch: 256
      partition: 32
    }
  ]
}

Step 3: Import data into NebulaGraph¶

Run the following command to import Oracle data into NebulaGraph. For a description of the parameters, see Options for import.

${SPARK_HOME}/bin/spark-submit --master "local" --class com.vesoft.nebula.exchange.Exchange <nebula-exchange-3.5.0.jar_path> -c <oracle_application.conf_path>

Note

JAR packages are available in two ways: compiled them yourself, or download the compiled .jar file directly.

For example:

${SPARK_HOME}/bin/spark-submit  --master "local" --class com.vesoft.nebula.exchange.Exchange  /root/nebula-exchange/nebula-exchange/target/nebula-exchange-3.5.0.jar  -c /root/nebula-exchange/nebula-exchange/target/classes/oracle_application.conf

You can search for batchSuccess.<tag_name/edge_name> in the command output to check the number of successes. For example, batchSuccess.follow: 300.

Step 4: (optional) Validate data¶

Users can verify that data has been imported by executing a query in the NebulaGraph client (for example, NebulaGraph Studio). For example:

LOOKUP ON player YIELD id(vertex);

Users can also run the SHOW STATS command to view statistics.

Step 5: (optional) Rebuild indexes in NebulaGraph¶

With the data imported, users can recreate and rebuild indexes in NebulaGraph. For details, see Index overview.

Last update: August 17, 2023

Element	Name	Property
Tag	`player`	`name string, age int`
Tag	`team`	`name string`
Edge Type	`follow`	`degree int`
Edge Type	`serve`	`start_year int, end_year int`