Version

    CloverDataWriter

    Short Description
    Ports
    Metadata
    CloverDataWriter Attributes
    Details
    Examples
    Compatibility
    See also

    Short Description

    CloverDataWriter writes data to files in our internal binary CloverDX data format.

    ComponentData outputInput portsOutput portsTransformationTransf. requiredJavaCTLAuto-propagated metadata
    CloverDataWriterCloverDX binary file10-1⨯⨯⨯⨯⨯

    Ports

    Port typeNumberRequiredDescriptionMetadata
    Input0✓For received data recordsAny
    Input0⨯For port writing. See Writing to Output Port.byte or cbyte

    Metadata

    CloverDataWriter does not propagate metadata.

    CloverDataWriter has no metadata template.

    Input metadata can have any metadata type.

    Output metadata of CloverDataWriter has one field. The field has datatype byte or cbyte.

    CloverDataWriter Attributes

    AttributeReqDescriptionPossible values
    Basic
    File URLyes

    The attribute specifying where received data will be written (CloverDX data file, dictionary). See Supported File URL Formats for Writers.

    		 
    Append 

    By default, new records overwrite the older ones. If set to true, new records are appended to the older records stored in the output file(s).

    		false (default) | true
    Advanced
    Create directories 

    By default, non-existing directories are not created. If set to true, they are created.

    		false (default) | true
    Compress level 

    Sets the compression level (0 - no compression, 1 - fastest compression, 9 - best compression).

    		1 (default) | 0-9
    Number of skipped records 

    The number of records to be skipped. See Selecting Output Records.

    		0-N
    Max number of records 

    The maximum number of records to be written to the output file. See Selecting Output Records.

    		0-N
    Records per file Limits the number of records written to one file.0-N
    Exclude fields 

    A sequence of field names separated by a semicolon that will not be written to the output.

    		any field(s), e.g. field1;field3
    Partition key 

    A sequence of field names separated by a semicolon defining the records distribution into different output files. Records with the same Partition key are written to the same output file. According to the selected Partition file tag, use the proper placeholder ($ or #) in the file name mask, see Partitioning Output into Different Output Files. Field(s) to be used in partitioning to several output files.

    		any field(s), e.g. field1;field3
    Partition lookup table  An ID of a lookup table serving for selecting records that should be written to output file(s). For more information, see Partitioning Output into Different Output Files. e.g. MyLookupTable001
    Partition file tag 

    By default, output files are numbered. If it is set to Key file tag, output files are named according to the values of Partition key or Partition output fields. For more information, see Partitioning Output into Different Output Files.

    		Number file tag (default) | Key file tag
    Partition output fields 

    Fields of Partition lookup table whose values serve to name output file(s). For more information, see Partitioning Output into Different Output Files.

    		 
    Partition unassigned file name  The name of a file into which the unassigned records should be written if there are any. If not specified, data records whose key values are not contained in Partition lookup table are discarded. For more information, see Partitioning Output into Different Output Files.  
    Sorted input  In case the partitioning into multiple output files is turned on, all output files are opened at once. This could lead to an undesirable memory footprint for many output files (thousands). Moreover, for example unix-based OS usually have a very strict limitation of number of simultaneously open files (1,024) per process. In case you run into one of these limitations, consider sorting the data according to a partition key using one of our standard sorting components and set this attribute to true. The partitioning algorithm does not need to keep all output files open, just the last one is open at one time. For more information, see Partitioning Output into Different Output Files. false (default) | true
    Create empty files 

    If set to false, prevents the component from creating an empty output file when there are no input records.

    		true (default) | false
    Deprecated
    Save metadata 

    This attribute is ignored since CloverETL 4.0.

    		false (default) | true
    Save index 

    This attribute is ignored since CloverETL 4.0.

    		false (default) | true

    Details

    CloverDataWriter internally uses compression by default. Additional zipping is redundant. See the Compress level attribute.

    CloverDataWriter can write maps and lists.

    With this component, you can write data in this internal format that allows fast access to data. CloverDataWriter is faster than FlatFileWriter.

    Examples

    Writing to CloverDX File
    Appending to Existing File
    Writing to non-existing Directories
    Skipping Leading Records
    Writing at most N records per file
    Omitting uninteresting fields
    Parting records into several files according to input field
    Parting records into several files according to input field using lookup table

    Writing to CloverDX File

    Write records to CloverDX file.

    Solution

    Set up the File URL attribute.

    AttributeValue
    File URL${DATAOUT_DIR}/my-clover-file.cdf

    If the file exists, the data in the file is overwritten.

    Appending to Existing File

    Append records of each graph run to an existing file my-clover-file.cdf.

    Solution

    Set up the File URL and Append attributes.

    AttributeValue
    File URL${DATAOUT_DIR}/my-clover-file.cdf
    Appendtrue

    Writing to non-existing Directories

    Write data to file my-clover-file.cdf in the cdrw directory. The directory may not exist.

    Solution

    Use the File URL and Create directories attributes.

    AttributeValue
    File URL${DATAOUT_DIR}/cdrw/my-clover-file.cdf
    Create directoriestrue

    Skipping Leading Records

    The first 10 records should be omitted. Write the rest of the records.

    Solution

    Use the File URL and Number of skipped records attributes.

    AttributeValue
    File URL${DATAOUT_DIR}/my-clover-file.cdf
    Number of skipped records10

    Writing at most N records per file

    Write at most 100 records.

    Solution

    Use the File URL and Max number of records attributes.

    AttributeValue
    File URL${DATAOUT_DIR}/my-clover-file.cdf
    Max number of records100

    Omitting uninteresting fields

    Metadata on the input edge of CloverDataWriter has fields ID, Firstname,Surname and Salary. Save a list containing Firstname and Surname to CloverDX data file employees.cdf.

    Solution

    Use the File URL and Exclude fields attributes.

    AttributeValue
    File URL${DATAOUT_DIR}/employees.cdf
    Exclude fieldsID;Salary

    Parting records into several files according to input field

    A list of students contains fields Firstname, Lastname and Mark. Categorize records into several files according to the mark. The created files will have names: students_A.cdf, ... students_F.cdf.

    Solution

    Use the File URL, Partition key and Partition file tag attributes.

    AttributeValue
    File URL${DATAOUT_DIR}/students_#.cdf
    Partition keyMark
    Partition file tagKey file tag

    Note: Records with students without mark will be saved into the students_.cdf file.

    Parting records into several files according to input field using lookup table

    The input data contains a number of active customers for particular countries. The countries are of different regions. Categorize records into the files according to the region. 

    CZ|105
UK|651
US|827
...

    The input metadata contains fields CountryCode and Customers but nothing in the record denotes the region directly. You have a list of country codes with corresponding region to be used for partitioning. 

    CZ|Europe
UK|Europe
US|America
...

    Some country codes may not be present in the list, store records with country codes not present in the list into a separate file region_missing.cdf.

    Solution

    Use the attributes File URL, Partition key, Partition lookup table, Partition file tag, Partition output fields, Partition unassigned file name. You need a lookup table CountryCodeRegion, too.

    AttributeValue
    File URL${DATAOUT_DIR}/region_#.cdf
    Partition keyCountryCode
    Partition lookup tableCountryCodeRegion
    Partition file tagKey file tag
    Partition output fieldsContinent
    Partition unassigned file namemissing

    The files region_Europe.cdf, region_America.cdf, ... and region_missing.cdf will be created.

    Compatibility

    VersionCompatibility Notice
    2.9

    CloverDataWriter also writes a header to output files with a version number. For this reason, CloverDataReader expects that files in CloverDX binary format contain such a header with the version number. CloverDataReader 2.9 cannot read files written by older versions of CloverDX nor these older versions can read data written by CloverDataWriter 2.9.

    4.0

    The internal structure of zip archive has changed, graphs relying on the structure will stop working. Graphs using a plain file URL without any internal entry specification are not affected. 

    zip:(${DATAIN_DIR}/customers.zip) - will work
zip:(${DATAIN_DIR}/customers.zip)#DATA/customers - won't work

    As CloverDX format can use compression internally, addition of next compression level is redundant.

    Values of parameters Save metadata and Save index are not used since CloverETL 4.0.

    4.4.0-M2

    CloverDataWriter can write to output port just to byte or cbyte field.