Stage functions

A stage usually has at least one data input or one data output. However, some stages can accept more than one data input, and output to more than one stage. The following table lists the available stages and gives details on their functions:

Table 1. Stages

Stage	Icon	Function
Aggregator		Classifies incoming data into groups, computes totals and other summary functions for each group, and passes them to another stage in the job.
Bloom Filter		Looks up incoming keys against previous values.
Change Apply		Applies encoded change operations to a before data set based on a changed data set. The before and after data sets come from the Change Capture stage.
Change Capture		Compares two data sets and makes a record of the differences.
Checksum		Generates a checksum value from the specified columns in a row and adds the checksum to the row.
Column Export		Exports data from a number of columns of different data types into a single column of data types ustring, string, or binary.
Column Generator		Adds columns to incoming data and generates mock data for these columns for each data row processed.
Column Import		Imports data from a single column and outputs it to one or more columns.
Combine Records		Combines records in which particular key-column values are identical into vectors of subrecords.
Compare		Performs a column-by-column comparison of records in two presorted input data sets.
Compress		Uses the UNIX compress or GZIP utility to compress a data set. It converts a data set from a sequence of records into a stream of raw binary data.
Copy		Copies a single input data set to a number of output data sets.
Decode		Decodes a data set by using a UNIX decoding command that you supply.
Difference		Performs a record-by-record comparison of two input data sets, which are different versions of the same data set.
Distributed Transaction		Runs transactions across multiple data sources.
Encode		Encodes a data set by using a UNIX encoding command that you supply.
Expand		Uses the UNIX uncompress or GZIP utility to expand a data set. It converts a previously compressed data set back into a sequence of records from a stream of raw binary data.
External Filter		Allows you to specify a UNIX command that acts as a filter on the data you are processing.
Filter		Transfers, unmodified, the records of the input data set that satisfy requirements that you specify and filters out all other records.
Funnel		Copies multiple input data sets to a single output data set.
Generic		Incorporates an Orchestrate® Operator in your job.
Head		Selects the first N records from each partition of an input data set and copies the selected records to an output data set.
Join		Performs join operations on two or more data sets input to the stage and then outputs the resulting data set.
Lookup		Used to perform lookup operations on a data set read into memory from any other Parallel job stage that can output data or provided by one of the database stages that support reference output links. It can also perform a look up on a lookup table that is contained in a Lookup File Set stage.
Make Subrecords		Combines specified vectors in an input data set into a vector of subrecords whose columns have the names and data types of the original vectors.
Make Vector		Combines specified columns of an input data record into a vector of columns.
Merge		Combines a sorted master data set with one or more sorted update data sets.
Modify		Alters the record schema of its input data set.
Peek		Prints record column values either to the job log or to a separate output link as the stage copies records from its input data set to one or more output data sets.
Pivot Enterprise		The Pivot Enterprise stage is a processing stage that pivots data horizontally and vertically. Horizontal pivoting maps a set of columns in an input row to a single column in multiple output rows. Vertical pivoting maps a set of rows in the input data to single or multiple output columns.
Promote Subrecords		Promotes the columns of an input subrecord to top-level columns.
Remove Duplicates		Takes a single sorted data set as input, removes all duplicate records, and writes the results to an output data set.
Row Generator		Produces a set of mock data fitting the specified meta data.
Sample		Samples an input data set.
Slowly Changing Dimension (SCD)		Works within the context of a star schema database to store and manage current and historical data over time.
Sort		Sorts input columns.
Split Subrecord		Separates an input subrecord field into a set of top-level vector columns.
Split Vector		Promotes the elements of a fixed-length vector to a set of similarly named top-level columns.
Surrogate Key Generator stage		Generates surrogate key columns and maintains the key source.
Switch		Takes a single data set as input and assigns each input record to an output data set based on the value of a selector field.
Tail		Selects the last N records from each partition of an input data set and copies the selected records to an output data set.
Transformer		Handles extracted data, performs any conversions that are required, and passes data to another active stage or a stage that writes data to a target database or file.
Wave Generator		Monitors a stream of data and inserts end-of-wave markers where needed.
Web Service		Accesses a web service operations within a DataStage flow or job.
Write Range Map		Writes data to a range map. The stage can have a single input link.

Watch this series of videos to see how to use the most common stages.