Record Header Attributes

Record header attributes are attributes in record headers that you can use in pipeline logic, as needed.

Some stages create record header attributes for a particular purpose. For example, CDC-enabled origins include the CRUD operation type in the sdc.operation.type record header attribute. This enables CRUD-enabled destinations to determine the operation type to use when processing records. Similarly, the Hive Metadata processor generates record header attributes that some destinations can use as part of the Drift Synchronization Solution for Hive.

Other stages include processing-related information in record header attributes for general use. For example, event-generating stages include the event type in record header attributes in case you want to process the event based on that information. And several origins include information such as the originating file name, location, or partition for each record.

You can use certain processors to create or update record header attributes. For example, you can use an Expression Evaluator to create attributes for record-based writes.

The inclusion of attributes in record headers does not require using them in the pipeline. You can, for example, use the CDC-enabled Salesforce origin in a non-CDC pipeline and ignore the CDC record header attributes that are automatically generated.

When writing data to destination systems, record header attributes are preserved with the record only when using the Google Pub/Sub Publisher or JMS Producer destination or when using another destination with the SDC Record data format. To preserve the information when using other data formats, use the Expression Evaluator to copy information from record header attributes to record fields.

Working with Header Attributes

You can use an Expression Evaluator processor or any scripting processor to create or update record header attributes. For example, the MongoDB destination requires a CRUD operation to be specified in a record header attribute. If the origin providing the data does not generate that information automatically, you can use an Expression Evaluator processor or any scripting processor to set the attribute value.

Record header attributes are string values. You can use record:attribute functions in any expression to include attribute values in calculations.

Important: Record header attributes do not have field paths. When using an attribute in an expression, use just the attribute name, surrounded by quotation marks since attributes are strings, as follows:

 ${record:attribute('<attribute name>')}

For example, the following Expression Evaluator adds the file and offset record header attributes created by the Directory origin to the record:

Internal Attributes

Data Collector generates and updates some read-only internal record header attributes as records move from stage to stage. These attributes can be viewed for debugging issues, but can only be updated by Data Collector.

The record:attribute function does not allow access to internal record header attributes. The following table describes the internal record header attributes and the functions that you can use to access the data in the pipeline:


Internal Record Header Attribute	Description	Related Function
stageCreator	The ID of the stage that created the record.	record:creator()
sourceId	Source of the record. Can include different information based on the origin type.	record:id()
stagesPath	List of stages that processed the record in order, by stage name.	record:path()
trackingId	The route the record has taken through the pipeline, starting with the sourceId, then listing the stages that processed the record.	n/a
previousTrackingId	The tracking ID of the record before it entered the current stage.	n/a
errorStage	The stage that generated the error. In error records only.	record:errorStage()
errorStageLabel	The user-defined name for a stage. In error records only.	record:errorStageLabel()
errorCode	The error code. In error records only.	record:errorCode()
errorJobId	The ID of the job that started the pipeline. Only in error records from pipelines started by Control Hub jobs.	n/a
errorMessage	The error message. In error records only.	record:errorMessage()
errorTimestamp	The time that the error occurred. In error records only.	record:errorTime()
errorStackTrace	The stack trace associated with the error. In error records only.	n/a

Header Attribute-Generating Stages

The following table lists the stages that generate record header attributes:


Stage	Description
CDC-enabled origins	Include the CRUD operation type in the sdc.operation.type header attribute and can include additional CRUD and CDC information in record header attributes. For more information, see CDC-Enabled Origins.
Origins that process Avro data and the Data Parser processor	Include the Avro schema in an avroSchema record header attribute.
Origins that process Parquet data	Include the Parquet schema in a parquetSchema record header attribute, and include the index number of the element in a union the data is read from in an `avro.union.typeIndex./id` record header attribute unless the origin is configured to skip union indexes.
Origins that process XML data	Can include namespaces in an xmlns record header attribute when you enable field XPaths.
Stages that generate events	Generate record header attributes for event records. For details about event record header attributes, see "Event Records" in the stage documentation.
Amazon S3 origin	Can be configured to include system-defined and user-defined object metadata in record header attributes.
Amazon SQS Consumer origin	Can be configured to include SQS message attributes in record header attributes.
Aurora PostgreSQL CDC Client origin	When tables have primary keys, includes information about the primary keys in record header attributes.
Azure Blob Storage origin	Can be configured to include system-defined, user-defined, and custom object metadata in record header attributes.
Azure Data Lake Storage Gen2 origin	Can be configured to include system-defined and custom object metadata in record header attributes.
Azure Data Lake Storage Gen2 (Legacy) origin	Includes information about the originating file for the record in record header attributes.
CONNX origin	Can be configured to include table and data type information in JDBC record header attributes.
CONNX CDC origin	Can be configured to include table and data type information in JDBC record header attributes.
Directory origin	Includes information about the originating file for the record in record header attributes.
File Tail origin	Includes information about the originating file for the record in record header attributes. Can be configured to use tag attributes for sets of files.
Google Pub/Sub Subscriber origin	When available, includes user-defined message attributes in record header attributes
Groovy Scripting origin	Can be configured to create record header attributes.
Hadoop FS Standalone origin	Includes information about the originating file for the record in record header attributes.
HTTP Client origin	Includes response header fields in record header attributes.
HTTP Server origin	Includes information about the requested URL and request header fields in record header attributes.
JavaScript Scripting origin	Can be configured to create record header attributes.
JDBC Multitable Consumer origin	Includes table and data type information in JDBC record header attributes.
JDBC Query Consumer origin	Can be configured to include table and data type information in JDBC record header attributes.
Jython Scripting origin	Can be configured to create record header attributes.
Kafka Multitopic Consumer origin	Includes information about the origins of the record in record header attributes. Can also include Kafka message headers in record header attributes.
MapR FS Standalone origin	Includes information about the originating file for the record in record header attributes.
MapR Multitopic Streams Consumer origin	Includes information about the origins of the record in record header attributes.
MapR Streams Consumer origin	Includes information about the origins of the record in record header attributes.
MQTT Subscriber origin	Includes information about the origins of the record in record header attributes.
MySQL Binary Log origin	When tables have primary keys, includes information about the primary keys in record header attributes.
Oracle CDC origin	When tables have primary keys, includes information about the primary keys in record header attributes. Can include a range of additional data depending on how you configure the origin.
Oracle CDC Client origin	When tables have primary keys, includes information about the primary keys in record header attributes.
Oracle Multitable Consumer origin	Includes table and data type information in JDBC Header Attributes.
PostgreSQL CDC Client origin	When tables have primary keys, includes information about the primary keys in record header attributes.
Pulsar Consumer (Legacy) origin	Includes information in the properties field of the message and the topic that the message was read from in record header attributes.
RabbitMQ Consumer origin	Includes RabbitMQ attributes in record header attributes.
REST Service origin	Includes information about the URL and request header fields in record header attributes.
Salesforce origin	Includes Salesforce information about the origins of the record in Salesforce header attributes.
Salesforce Bulk API 2.0 origin	Includes Salesforce information about the origins of the record in Salesforce header attribute.
SAP HANA Query Consumer origin	Can be configured to include table and data type information in JDBC header attributes. Can be configured to include SAP HANA connection information in SAP HANA header attributes.
SFTP/FTP/FTPS Client origin	Includes information about the originating file for the record in record header attributes.
Snowflake Bulk origin	Includes information about the origins of the record in Snowflake header attributes.
Couchbase Lookup processor	Includes information about the state of the looked-up document in a record header attribute.
Expression Evaluator processor	Can be configured to create or update record header attributes.
Groovy Evaluator processor	Can be configured to create or update record header attributes.
Hive Metadata processor	Generates record header attributes for the data record. These attributes can be used for record-based writes as part of the Drift Synchronization Solution for Hive. Can be configured to add custom header attributes to the metadata record.
HTTP Client processor	Includes response header fields in record header attributes. Generates record header attributes when passing an incoming record downstream based on per-status action or timeout properties.
JavaScript Evaluator processor	Can be configured to create or update record header attributes.
Jython Evaluator processor	Can be configured to create or update record header attributes.
Schema Generator processor	Generates schemas and writes them to a user-defined record header attribute.
Aerospike Client destination	Generates error record header attributes for records that cannot be written.

Record Header Attributes for Record-Based Writes

Destinations can use information in record header attributes to write data. Destinations that write Avro data can use Avro schemas in the record header. The Hadoop FS and MapR FS destinations can use record header attributes to determine the directory to write to and when to roll a file as part of the Drift Synchronization Solution for Hive. For more information, see Drift Synchronization Solution for Hive.

To use a record header attribute, configure the destination to use the header attribute and ensure that the records include the header attribute.

The Hive Metadata processor automatically generates record header attributes for Hadoop FS and MapR FS to use as part of the Drift Synchronization Solution for Hive. For all other destinations, you can use the Expression Evaluator or a scripting processor to add record header attributes.

You can use the following record header attributes in destinations:

targetDirectory attribute in all the Azure Data Lake Storage destinations and in the Hadoop FS, Local FS, and MapR FS destinations: The targetDirectory record header attribute defines the directory where the record is written. If the directory does not exist, the destination creates the directory. The targetDirectory header attribute replaces the Directory Template property in the destination.; When you use targetDirectory to provide the directory, the time basis configured for the destination is used only for determining whether a record is late. Time basis is not used to determine the output directories to create or to write records to directories.; To use the targetDirectory header attribute, on the Output tab, select Directory in Header.
avroSchema attribute in destinations that write Avro data: The avroSchema header attribute defines the Avro schema for the record. When you use this header attribute, you cannot define an Avro schema to use in the destination.; To use the avroSchema header attribute, on the Data Format tab, select the Avro data format, and then for the Avro Schema Location property, select In Record Header.
parquetSchema attribution in destinations that write Parquet data: The parquetSchema header attribute defines the Parquet schema for the record. When you use this header attribute, you cannot define a Parquet schema to use in the destination.; To use the parquetSchema header attribute, on the Data Format tab, select the Parquet data format, and then for the Parquet Schema Location property, select In Record Header.
roll attribute in all the Azure Data Lake Storage destinations and in the Hadoop FS, Local FS, and MapR FS destinations: The roll attribute, when present in the record header, triggers a roll of the file.; You can define the name of the roll header attribute. When you use the Hive Metadata processor to generate the roll header attribute, use the default "roll" attribute name. When you use an Expression Evaluator, use the name of the roll attribute that you defined in the processor.; To use a roll header attribute, on the Output tab, select Use Roll Attribute and define the name of the attribute.

Generating Attributes for Record-Based Writes

You can use the Hive Metadata processor, an Expression Evaluator processor or any scripting processor to generate record header attributes for record-based writes. The Hive Metadata processor automatically generates record header attributes for Hadoop FS and MapR FS to use as part of the Drift Synchronization Solution for Hive. For all other destinations, you can use the Expression Evaluator or a scripting processor to add record header attributes.

To use an Expression Evaluator processor or any scripting processor, you must generate record header attributes as expected by the destination. Use the following guidelines to generate record header attributes:

Generating the target directory

When using an Expression Evaluator processor or any scripting processor to generate the target directory, note the following details:

The destination expects the directory in a header attribute named "targetDirectory".
The destination uses the directory exactly as written in the targetDirectory header attribute. Unlike directory templates, the directory specified in the targetDirectory attribute should not include any components that require evaluation, such as runtime parameters, variables, or runtime properties.
When you define the expression that evaluates to a directory, you can use any valid component, including expressions that evaluate data in the record.

For example, you want to write records to different directories based on the Data Collector that runs the pipeline, and the region and store ID where the transaction took place. You can set up a runtime resource named DIR that defines the base for the directory and define DIR for each Data Collector that runs the pipeline. Then, you can use the following expression in the Expression Evaluator to define the targetDirectory attribute:

${runtime:conf('DIR')/transactions/${record.value('/region')}/${record.value('/storeID')}

Generating the Avro schema

When using an Expression Evaluator processor or any scripting processor to generate the Avro schema, note the following details:

The destination expects the Avro schema in a header attribute named "avroSchema".

Use the standard Avro schema format, for example:

{"type":"record","name":"table_name","namespace":"database_name",
"fields":[{"name":"int_val","type":["null","int"],"default":null},
{"name":"str_val","type":["null","string"],"default":null}]}

The database name and table name must be included in the Avro schema.

Tip: You might use an Avro schema generator to help generate the Avro schema.

Generating the roll attribute

When using an Expression Evaluator processor or any scripting processor to generate the roll attribute, note the following details:

Use any name for the attribute and specify the attribute name in the destination.
Configure an expression that defines when to roll files.

To define these record header attributes in the Expression Evaluator, perform the following steps:

On the Expressions tab of the Expression Evaluator, specify the Header Attribute name.
To generate a target directory, use targetDirectory.
To generate an Avro schema, use avroSchema.
You can use any name for a roll indicator header attribute.
For the Header Attribute Expression, define the expression that evaluates to the information you want the destination to use.

For information about generating record header attributes with scripting processors, see the scripting processor documentation.

Viewing Attributes in Data Preview

You can use data preview to view the record header attributes associated with a record at any given point in the pipeline. To view record header attributes, enable the Show Record/Field Header data preview property.

For example, the following image shows a record generated by the Directory origin in data preview.

The "Record Header" list displays the set of read-only internal attributes in the record at this point of the pipeline. The header attributes under "values" are the attributes created by the Directory origin.