- Sequential files, unlike most other data sources, do not have inherent column definitions, and so DataStage cannot always tell where there are extra columns that need propagating. You can only use RCP on sequential files if you have used the Schema File property to specify a schema which describes all the columns in the sequential file.
- Used to read complex flat files from mainframe machine buy using Complex Flat File Stage. Sequential File, Aggregator, ODBC, Transformer, Hashed-File, Oracle OCI, XML, Folder, FTP Plug-in Stages were extensively used to develop the server jobs. Use the EXPLAIN PLAN statement to determine the execution plan Oracle Database.
- Editing a Complex Flat File stage as a target To edit a CFF stage as a target, you must provide details about the file that the stage will write, define the record format of the data, and define the column metadata. Reject links The Complex Flat File stage can have a single reject link, whether you use the stage as a source or a target.
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The Complex Flat File stage lets you convert data extracted from complex flat files that are generated on an IBM® mainframe. A complex flat file has hierarchical structure in its arrangement of columns. It is physically flat (that is, it has no pointers or other complicated infrastructure), but logically represents parent-child relationships. You can use multiple record types to achieve this hierarchical structure.
RECOGNIZING A HIERARCHICAL STRUCTURE
For example, use records with various structures for different types of information, such as an 'E' record for employee static information, and a 'S' record for employee monthly payroll information, or for repeating groups of information (twelve months of revenue). You can also combine these record groupings, and in the case of repeating data, you can flatten nested OCCURS groups.
MANAGING REPEATING GROUPS AND INTERNAL STRUCTURES
You can easily load, manage, and use repeating groups and internal record structures such as GROUP fields and OCCURS. You can ignore GROUP data columns that are displayed as raw data and have no logical use for most applications. The metadata can be flattened into a normalized set of columns at load time, so that no arrays exist at run time.
Complex Flat File Stage Datastage Example Programs Download
SELECTING SUBSETS OF COLUMNS
You can select a subset of columns from a large COBOL File Description (CFD). This filtering process results in performance gains since the stage no longer parses and processes hundreds of columns if you only need a few.
Complex flat files can also include legacy data types.
OUTPUT LINKS
The Complex Flat File stage supports multiple outputs. An output link specifies the data you are extracting, which is a stream of rows to be read.
When using the Complex Flat File stage to process a large number of columns, for example, more than 300, use only one output link in your job. This dramatically improves the performance of the GUI when loading, saving, or building these columns. Having more than one output link causes a save or load sequence each time you change tabs.
The Complex Flat File stage does not support reference lookup capability or input linksInfoSphere DataStage is also flexible about meta data. It can cope with the situation where meta data is not fully defined.
You can define part of your schema and specify that, if your job encounters extra columns that are not defined in the meta data when it actually runs, it will adopt these extra columns and propagate them through the rest of the job.
This is known as Runtime Column Propagation (RCP).
RCP can be enabled for a project via the Administrator client, and set for individual links via the Output Page Columns tab for most stages, or in the Output page General tab for Transformer stages.
You should always ensure that runtime column propagation is turned on if you want to use schema files to define column meta data.
When we run the Datastage Jobs, the columns may change from one stage to another stage. At that point of time we will be loading the unnecessary columns in to the stage, which is not required.
If we want to load the required columns to load into the target, we can do this by enabling a RCP.
Complex Flat File Stage Datastage Example Programs Download
If we enable RCP, we can send the required columns into the target.
RCP is mostly useful when we use reusable job where different metadata comes into the picture.
Using RCP With Sequential Stages
Runtime column propagation (RCP) allows DataStage to be flexible about the columns you define in a job.
If RCP is enabled for a project, you can just define the columns you are interested in using in a job, but ask DataStage to propagate the other columns through the various stages.
So such columns can be extracted from the data source and end up on your data target without explicitly being operated on in between.
Read also: When should we use Sparse Lookup or Join in DataStage?
Sequential files, unlike most other data sources, do not have inherent column definitions, and so DataStage cannot always tell where there are extra columns that need propagating.
You can only use RCP on sequential files if you have used the Schema File property to specify a schema which describes all the columns in the sequential file.
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You need to specify the same schema file for any similar stages in the job where you want to propagate columns. Stages that will require a schema file are:
- Sequential File
- File Set
- External Source
- External Target
- Column Import
- Column Export