CloverDataWriter

CloverDataWriter 64x64

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.

Data output Input ports Output ports Transformation Transf. required Java CTL Auto-propagated metadata

CloverDX binary file

1

0-1

Ports

Port type Number Required Description Metadata

Input

0

For received data records

Any

Output

0

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

Attribute Req Description Possible values

Basic

File URL

yes

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

Secret key

Key to use for encryption of files. Specifying the key enables encryption. Enabling encryption automatically disables compression.

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, lists and variants.

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.

Attribute Value

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.

Attribute Value

File URL

${DATAOUT_DIR}/my-clover-file.cdf

Append

true

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.

Attribute Value

File URL

${DATAOUT_DIR}/cdrw/my-clover-file.cdf

Create directories

true

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.

Attribute Value

File URL

${DATAOUT_DIR}/my-clover-file.cdf

Number of skipped records

10

Writing at most N records per file

Write at most 100 records.

Solution

Use the File URL and Max number of records attributes.

Attribute Value

File URL

${DATAOUT_DIR}/my-clover-file.cdf

Max number of records

100

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.

Attribute Value

File URL

${DATAOUT_DIR}/employees.cdf

Exclude fields

ID;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.

Attribute Value

File URL

${DATAOUT_DIR}/students_#.cdf

Partition key

Mark

Partition file tag

Key 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.

Attribute Value

File URL

${DATAOUT_DIR}/region_#.cdf

Partition key

CountryCode

Partition lookup table

CountryCodeRegion

Partition file tag

Key file tag

Partition output fields

Continent

Partition unassigned file name

missing

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

Compatibility

Version Compatibility 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.