Processors

A processor stage represents a type of data processing that you want to perform. You can use as many processors in a pipeline as you need.

You can use different processors based on the execution mode of the pipeline: standalone, cluster. To help create or test pipelines, you can use development processors.

Standalone Pipelines Only

In standalone pipelines, you can use the following processor:

Record Deduplicator - Removes duplicate records.

Standalone or Cluster Pipelines

In standalone or cluster pipelines, you can use the following processors:

Base64 Field Decoder - Decodes Base64 encoded data to binary data.
Base64 Field Encoder - Encodes binary data using Base64.
Control Hub API - Calls a Control Hub API. This is an orchestration stage.
Couchbase Lookup - Performs lookups in Couchbase Server to enrich records with data.
Data Generator - Serializes a record into a field using the specified data format.
Data Parser - Parses NetFlow or syslog data embedded in a field.
Delay - Delays passing a batch to the rest of the pipeline.
Encrypt and Decrypt Fields - Encrypts or decrypts fields.
Expression Evaluator - Performs calculations on data. Can also add or modify record header attributes.
Field Flattener - Flattens nested fields.
Field Hasher - Uses an algorithm to encode sensitive data.
Field Mapper - Maps an expression to a set of fields to alter field paths, field names, or field values.
Field Masker - Masks sensitive string data.
Field Merger - Merges fields in complex lists or maps.
Field Order - Orders fields in a map or list-map root field type and outputs the fields into a list-map or list root field type.
Field Pivoter - Pivots data in a list, map, or list-map field and creates a record for each item in the field.
Field Remover - Removes fields from a record.
Field Renamer - Renames fields in a record.
Field Replacer - Replaces field values.
Field Splitter - Splits the string values in a field into different fields.
Field Type Converter - Converts the data types of fields.
Field Zip - Merges list data from two fields.
Geo IP- Returns geolocation and IP intelligence information for a specified IP address.
Groovy Evaluator - Processes records based on custom Groovy code.
HBase Lookup - Performs key-value lookups in HBase to enrich records with data.
Hive Metadata - Works with the Hive Metastore destination as part of the Drift Synchronization Solution for Hive.
HTTP Client - The HTTP Client processor sends requests to an HTTP resource URL and writes the results to a field.
HTTP Router - Routes data to different streams based on the HTTP method and URL path in record header attributes.
JavaScript Evaluator - Processes records based on custom JavaScript code.
JDBC Lookup - Performs lookups in a database table through a JDBC connection.
JDBC Tee - Writes data to a database table through a JDBC connection, and enriches records with data from generated database columns.
JSON Generator - Serializes data from a field to a JSON-encoded string.
JSON Parser - Parses a JSON object embedded in a string field.
Jython Evaluator - Processes records based on custom Jython code.
Kaitai Struct Parser - Parses binary data using a Kaitai Struct format description file.
Kudu Lookup - Performs lookups in Kudu to enrich records with data.
Log Parser - Parses log data in a field based on the specified log format.
MLeap Evaluator - Uses a machine learning model stored in an MLeap bundle to generate evaluations, scoring, or classifications of data.
MongoDB Lookup - Performs lookups in MongoDB to enrich records with data.
PMML Evaluator - Uses a machine learning model stored in a PMML document to generate predictions or classifications of data.
PostgreSQL Metadata - Tracks structural changes in source data then creates and alters PostgreSQL tables as part of the Drift Synchronization Solution for PostgreSQL.
Redis Lookup - Performs key-value lookups in Redis to enrich records with data.
Salesforce Bulk API 2.0 Lookup - Performs lookups in Salesforce using Salesforce Bulk API 2.0.
Salesforce Lookup - Performs lookups in Salesforce using the SOAP or Bulk API.
Schema Generator - Generates a schema for each record and writes the schema to a record header attribute.
SQL Parser - Parses SQL queries in a string field.
Start Jobs - Starts one or more Control Hub jobs in parallel. This is an orchestration stage.
Static Lookup - Performs key-value lookups in local memory.
Stream Selector - Routes data to different streams based on conditions.
TensorFlow Evaluator - Uses a TensorFlow machine learning model to generate predictions or classifications of data.
Wait for Jobs - Waits for Control Hub jobs to complete. This is an orchestration stage.
Web Client - Sends requests to an HTTP endpoint and writes the results to a field.
Whole File Transformer - Transforms Avro files to Parquet.
Windowing Aggregator - Performs aggregations within a window of time, displays the results in Monitor mode, and writes the results to events when enabled. This processor does not update the records being evaluated.
XML Flattener - Flattens XML data in a string field.
XML Parser - Parses XML data in a string field.

Development Processors

To help create or test pipelines, you can use the following development processors:

Dev Identity
Dev Random Error
Dev Record Creator

For more information, see Development Stages.