PIPELINES

information_schema.PIPELINES Schema

Column Name	Description
`DATABASE_NAME`	The name of the database associated with the pipeline.
`PIPELINE_NAME`	The name of the pipeline.
`PIPELINE_ID`	The unique `ID` of the pipeline.
`CONFIG_JSON`	The pipeline's configuration in JSON format. This JSON is read only, and it is automatically generated when your pipeline configuration changes. The JSON schema for this column is described in CONFIG_JSON Schema, and is intended for use in a Web-based application (such as MemSQL Ops with SingleStore versions earlier than 7.5).
`STATE`	The current state of the pipeline. Possible values are `Running`, `Error`, and `Stopped`. `Running`: The pipeline is currently running. If the `pipelines_stop_on_error` variable is set to `ON`, the pipeline has not encountered any errors during extraction, transformation, or loading. `Error`: The pipeline encountered an error and is currently stopped. When a pipeline is in the `Error` state, it must be manually started.If the `pipelines_stop_on_error` variable is set to `OFF`, a pipeline cannot enter the `Error` state. The pipeline will remain in the `Running` state until it’s manually stopped, and any errors that occur will be written to the `information_schema.PIPELINES_ERRORS` table. `Stopped`: The pipeline is currently stopped. The pipeline can only enter the `Stopped` state due to manual intervention.
`SKIPPED_BATCH_PARTITIONS`	The sum of the number of batches that have been skipped in the pipeline. Batches may be skipped if the maximum number of batch retries was reached, which is set using the `pipelines_max_retries_per_batch_partition` variable.
`CREATE_TIME`	The date/time when the pipeline was created or recreated by the `CREATE PIPELINE` or `CREATE OR REPLACE PIPELINE` statements.
`ALTER_TIME`	The date/time when the pipeline was altered by an `ALTER PIPELINE` statement.

CONFIG_JSON Schema

The CONFIG_JSON column in the information_schema.PIPELINES table contains a fixed set of read-only JSON key/value pairs. Some of these JSON values can also be seen by executing the SHOW CREATE PIPELINE <pipeline-name> statement. Each key/value pair is described below.

Example `CONFIG_JSON` for Kafka Pipelines

JSON

{
   "name":"mypipeline",
   "source_type":"KAFKA",
   "connection_string":"172.17.0.2\/test-topic",
   "batch_interval":0,
   "transform":["http:\/\/127.0.0.1:8000\/transform.py","",""],
   "dup_key_policy":null,
   "table":"messages",
   "fields_terminated_by":"\t",
   "fields_enclosed_by":"",
   "fields_escaped_by":"\\",
   "lines_terminated_by":"\n",
   "lines_starting_by":"",
   "extended_null":false,
   "column_list":null,
   "on_duplicate_key_update":null,
   "running":false
}

Example `CONFIG_JSON` for S3 Pipelines

JSON

{
    "name": "my-s3-pipeline",
    "source_type": "S3",
    "connection_string": "my-s3-bucket-name",
    "config": "{\"region\": \"us-west-1\"}",
    "credentials": "{"aws_access_key_id": "your_access_key_id",
                      "aws_secret_access_key": "your_secret_access_key",
                      "aws_session_token": "your_temp_session_token",
                      "aws_web_identity_token": "your_aws_web_identiy_token",
                      "role_arn":"your_role_arn"}",
    "batch_interval": 2500,
    "max_partitions_per_batch": -1,
    "transform": null,
    "load_error_policy": null,
    "dup_key_policy": null,
    "table": "my_table_name",
    "fields_terminated_by": ",",
    "fields_enclosed_by": "",
    "fields_escaped_by": "\\",
    "lines_terminated_by": "\n",
    "lines_starting_by": "",
    "extended_null": false,
    "column_list": null,
    "on_duplicate_key_update": null
}

CONFIG_JSON Schema Definition

Key Name	Value Description
`name`	The name of the pipeline.
`source_type`	The data source type for the pipeline.
`connection_string`	The connection string (information varies depending on the type of pipeline).
`config`	The configuration information provided when creating a pipeline.
`credentials`	A JSON object containing properties for the pipeline authentication/authorization. The exact information included varies depending on the type of pipeline. For users with SUPER permission the field shows the credentials used on pipeline creation and for users with lesser permissions the field shows "`<CREDENTIALS REDACTED>`".
`batch_interval`	The time duration in milliseconds between batch extraction operations.
`transform`	The transform's URI, executable entry point, and arguments.
`load_error_policy`	The load error policy for the pipeline. For example, if `IGNORE` or `SKIP ... ERRORS` was specified during pipeline creation, they will appear as a JSON key/value pair like so: `{"load_error_policy": "skip_all_errors"}`
`dup_key_policy`	The duplicate key policy that indicates how a row should be inserted if it contains a duplicate key value.
`table`	The name of the table in which to insert data.
`fields_terminated_by`	The character that terminates a field.
`fields_enclosed_by`	The character that encloses a field.
`fields_escaped_by`	The character that escapes a field.
`lines_terminated_by`	The character that terminates a line.
`lines_starting_by`	The string prefix for a line.
`extended_null`	Specifies whether the non-quoted and case-insensitive string `null` will be loaded as a null type.
`column_list`	The column list to load data into.
`on_duplicate_key_update`	Specifies whether duplicate keys will be updated or ignored.
`running`	Specifies whether the pipeline is currently running. Current state of the pipeline is either `running`, `testing`, `profiling`, `running...foreground`, `error`, or `stopped`.

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information_schema.PIPELINES Schema

CONFIG_JSON Schema

Example `CONFIG_JSON` for Kafka Pipelines

Example `CONFIG_JSON` for S3 Pipelines

CONFIG_JSON Schema Definition

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PIPELINES

On this page

information_schema.PIPELINES Schema

CONFIG_JSON Schema

Example CONFIG_JSON for Kafka Pipelines

Example CONFIG_JSON for S3 Pipelines

CONFIG_JSON Schema Definition

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On this page

Was this article helpful?

Example `CONFIG_JSON` for Kafka Pipelines

Example `CONFIG_JSON` for S3 Pipelines