Version
CloverDataWriter
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. |
|
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 |
false (default) | true |
|
Advanced |
|||
Create directories |
By default, non-existing directories are not created.
If set to |
false (default) | true |
|
Compress level |
Sets the compression level ( |
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 |
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 |
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
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. 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 |