Help Center> Data Lake Insight> API Reference> Flink Job-related APIs> Generating a Static Stream Graph for a Flink SQL Job
Updated on 2024-05-22 GMT+08:00

Generating a Static Stream Graph for a Flink SQL Job

Function

This API is used to generate a static stream graph for a Flink SQL job.

Flink 1.15 does not support the generation of static stream graphs.

URI

  • URI format

    POST /v3/{project_id}/streaming/jobs/{job_id}/gen-graph

  • Parameter description
    Table 1 URI parameter

    Parameter

    Mandatory

    Type

    Description

    project_id

    Yes

    String

    Project ID, which is used for resource isolation. For details about how to obtain its value, see Obtaining a Project ID.

Request

Table 2 Request parameters

Parameter

Mandatory

Type

Description

sql_body

Yes

String

SQL

cu_number

No

Integer

Total number of CUs used by the job configured on the job editing page, which should match the actual number of CUs used. The actual number of CUs used is determined by the number of parallel operators.

Total number of CUs used by the job = Number of manager CUs + (Total number of concurrent operators / Number of slots of a TaskManager) x Number of TaskManager CUs

manager_cu_number

No

Integer

Number of CUs of the management unit.

parallel_number

No

Integer

Maximum degree of parallelism.

Concurrent tasks of each job operator. Appropriately increasing the value will improve the overall computing performance of a job. Considering switchover overheads due to increasing threads, the maximum value is four times the number of CUs. One to two times the number of CUs is the optimal.

tm_cus

No

Integer

Number of CUs in a taskManager.

tm_slot_num

No

Integer

Number of slots in a taskManager.

operator_config

No

String

Operator configurations.

You can call this API to obtain the operator ID. That is, the ID in operator_list contained in stream_graph in the response message is the operator ID.

static_estimator

No

Boolean

Whether to estimate static resources.

If this parameter is set to true, resources used by the job are estimated based on the operator ID and traffic.

static_estimator_config

No

String

Traffic or hit ratio of each operator, which is a string in JSON format.

This parameter is mandatory when static_estimator is set to true. During the configuration, the operator ID and operator traffic configuration are required.

  • You can call this API to obtain the operator ID. That is, the ID in operator_list contained in stream_graph in the response message is the operator ID.
  • The operator traffic is estimated based on the actual service conditions.

job_type

No

String

Job types.

Only flink_opensource_sql_job job is supported.

graph_type

No

String

Stream graph type. Currently, the following two types of stream graphs are supported:

  • simple_graph: Simplified stream graph
  • job_graph: Static stream graph

flink_version

No

String

Flink version. Currently, only 1.10 and 1.12 are supported.

Response

Table 3 Response parameters

Parameter

Mandatory

Type

Description

is_success

Yes

Boolean

Indicates whether the request is successfully executed. Value true indicates that the request is successfully executed.

message

Yes

String

System prompt. If execution succeeds, the message may be left blank.

error_code

Yes

String

Error codes.

stream_graph

Yes

String

Description of a static stream graph.

Example Request

Generate a static stream graph for a Flink SQL job.

{
  "job_type": "flink_opensource_sql_job",
  "graph_type": "job_graph",
  "sql_body": "create table orders(\r\n  name string,\r\n  num int\r\n) with (\r\n  'connector' = 'datagen',\r\n  'rows-per-second' = '1', --Generates a data record per second.\r\n  'fields.name.kind' = 'random', --Specify a random generator for the user_id field.\r\n  'fields.name.length' = '5' --Limit the length of user_id to 3.\r\n);\r\n \r\nCREATE TABLE sink_table (\r\n  name string,\r\n  num int\r\n) WITH (\r\n   'connector' = 'print'\r\n);\r\nINSERT into sink_table SELECT * FROM orders;",
  "cu_number": 2,
  "manager_cu_number": 1,
  "parallel_number": 2,
  "tm_cus": 1,
  "tm_slot_num": 0,
  "operator_config": "",
  "static_estimator": true,
  "flink_version": "1.12",
  "static_estimator_config": "{\"operator_list\":[{\"id\":\"0a448493b4782967b150582570326227\",\"output_rate\":1000},{\"id\":\"bc764cd8ddf7a0cff126f51c16239658\",\"output_rate\":1000}]}"
}

Example Response

{
    "message": "",
    "is_success": true,
    "error_code": "",
    "stream_graph": "{\n  \"jid\" : \"44334c4259f6714bddef1ac525364052\",\n  \"name\" : \"InternalJob_1715392878428\",\n  \"nodes\" : [ {\n    \"id\" : \"0a448493b4782967b150582570326227\",\n    \"parallelism\" : 1,\n    \"operator\" : \"\",\n    \"operator_strategy\" : \"\",\n    \"description\" : \"Sink: Sink(table=[default_catalog.default_database.sink_table], fields=[name, num])\",\n    \"chain_operators_id\" : [ \"0a448493b4782967b150582570326227\" ],\n    \"inputs\" : [ {\n      \"num\" : 0,\n      \"id\" : \"bc764cd8ddf7a0cff126f51c16239658\",\n      \"ship_strategy\" : \"FORWARD\",\n      \"exchange\" : \"pipelined_bounded\"\n    } ],\n    \"optimizer_properties\" : {}\n  }, {\n    \"id\" : \"bc764cd8ddf7a0cff126f51c16239658\",\n    \"parallelism\" : 2,\n    \"operator\" : \"\",\n    \"operator_strategy\" : \"\",\n    \"description\" : \"Source: TableSourceScan(table=[[default_catalog, default_database, orders]], fields=[name, num])\",\n    \"chain_operators_id\" : [ \"bc764cd8ddf7a0cff126f51c16239658\" ],\n    \"optimizer_properties\" : {}\n  } ],\n  \"operator_list\" : [ {\n    \"id\" : \"0a448493b4782967b150582570326227\",\n    \"name\" : \"Sink: Sink(table=[default_catalog.default_database.sink_table], fields=[name, num])\",\n    \"type\" : \"Sink\",\n    \"contents\" : \"Sink(table=[default_catalog.default_database.sink_table], fields=[name, num])\",\n    \"parallelism\" : 1,\n    \"tags\" : \"[SINK]\",\n    \"input_operators_id\" : [ \"bc764cd8ddf7a0cff126f51c16239658\" ]\n  }, {\n    \"id\" : \"bc764cd8ddf7a0cff126f51c16239658\",\n    \"name\" : \"Source: TableSourceScan(table=[[default_catalog, default_database, orders]], fields=[name, num])\",\n    \"type\" : \"Source\",\n    \"contents\" : \"TableSourceScan(table=[[default_catalog, default_database, orders]], fields=[name, num])\",\n    \"parallelism\" : 2,\n    \"tags\" : \"[PROCESS, UDF]\",\n    \"input_operators_id\" : [ ]\n  } ]\n}"
}

To make it easier to view the response information, we format stream_graph as follows:

    "jid": "65b6a7b0c1ad95b1722a92b49d2f6eba",
    "name": "InternalJob_1715392245413",
    "nodes": [
        {
            "id": "0a448493b4782967b150582570326227",
            "parallelism": 1,
            "operator": "",
            "operator_strategy": "",
            "description": "Sink: Sink(table=[default_catalog.default_database.sink_table], fields=[name, num])",
            "chain_operators_id": [
                "0a448493b4782967b150582570326227"
            ],
            "inputs": [
                {
                    "num": 0,
                    "id": "bc764cd8ddf7a0cff126f51c16239658",
                    "ship_strategy": "FORWARD",
                    "exchange": "pipelined_bounded"
                }
            ],
            "optimizer_properties": {

            }
        },
        {
            "id": "bc764cd8ddf7a0cff126f51c16239658",
            "parallelism": 2,
            "operator": "",
            "operator_strategy": "",
            "description": "Source: TableSourceScan(table=[[default_catalog, default_database, orders]], fields=[name, num])",
            "chain_operators_id": [
                "bc764cd8ddf7a0cff126f51c16239658"
            ],
            "optimizer_properties": {

            }
        }
    ],
    "operator_list": [
        {
            "id": "0a448493b4782967b150582570326227",
            "name": "Sink: Sink(table=[default_catalog.default_database.sink_table], fields=[name, num])",
            "type": "Sink",
            "contents": "Sink(table=[default_catalog.default_database.sink_table], fields=[name, num])",
            "parallelism": 1,
            "tags": "[SINK]",
            "input_operators_id": [
                "bc764cd8ddf7a0cff126f51c16239658"
            ]
        },
        {
            "id": "bc764cd8ddf7a0cff126f51c16239658",
            "name": "Source: TableSourceScan(table=[[default_catalog, default_database, orders]], fields=[name, num])",
            "type": "Source",
            "contents": "TableSourceScan(table=[[default_catalog, default_database, orders]], fields=[name, num])",
            "parallelism": 2,
            "tags": "[PROCESS, UDF]",
            "input_operators_id": [

            ]
        }
    ]
}

Status Codes

Table 4 describes status codes.

Table 4 Status codes

Status Code

Description

200

The operation is successful.

400

The input parameter is invalid.

Error Codes

If an error occurs when this API is invoked, the system does not return the result similar to the preceding example, but returns the error code and error information. For details, see Error Codes.