D toc

This section contains information on the fie formats and compression schemes that are supported for input to and output of 

D s product
r true

. 

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NOTE: To work with formats that are proprietary to a desktop application, such as Microsoft Excel, you do not need the supporting application installed on your desktop.

Native Input File Formats

D s product
r true

 can read and import directly these file formats:

• Excel (XLS/XLSX)

  Tip
  Tip: You may import multiple worksheets from a single workbook at one time. See Import Excel Data.

• CSV

• JSON, including nested

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  NOTE: D s product requires that JSON files be submitted with one valid JSON object per line. Consistently malformed JSON objects or objects that overlap linebreaks might cause import to fail. See Initial Parsing Steps.

• Plain Text
• LOG
• TSV

• Parquet

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  NOTE: When working with datasets sourced from Parquet files, lineage information and the $sourcerownumber reference are not supported.

• XML

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  NOTE: XML files can be ingested as unstructured text. XML support is not enabled by default. For more information, please contact D s proserv .

• Avro

For more information on data is handled initially, see Initial Parsing Steps.

Native Output File Formats

D s product

 can write to these file formats:

• CSV
• JSON

• Tableau (TDE)

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  NOTE: Publication of results in TDE format may require additional configuration. See below.

• Avro

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  NOTE: The D s photon and Spark running environments apply Snappy compression to this format.

• Parquet

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  NOTE: The D s photon and Spark running environments apply Snappy compression to this format.

Compression Algorithms

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NOTE: Importing a compressed file with a high compression ratio can overload the available memory for the application. In such cases, you can decompress the file before uploading. If decompression fails, you should contact your administrator about increasing the Java Heap Size memory.

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NOTE: Publication of results in Snappy format may require additional configuration. See below.

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NOTE: GZIP files on Hadoop are not split across multiple nodes. As a result, jobs can crash when processing it through a single Hadoop task. This is a known issue with GZIP on Hadoop. Where possible, limit the size of your GZIP files to 100 MB of less, or use BZIP2 as an alternative compression method. As a workaround, you can try to run the job on the unzipped file. You may also disable profiling for the job. See Run Job Page.

Read Native File Formats

Write Native File Formats

Additional Configuration for File Format Support

Publication of some formats requires execute permissions

When job results are generated and published in the following formats, the

D s platform

includes a JAR, from which is extracted a binary executable into a temporary directory. From this directory, the binary is then executed to generate the results in the proper format. By default, this directory is set to /tmp on the

D s node

.

In many environments, execute permissions are disabled on /tmp for security reasons. Use the steps below to specify the temporary directory where this binary can be moved and executed.

Steps:

1. Login to the application as an administrator.
2. From the menu, select Settings menu > Settings > Admin Settings.

3. For each of the following file formats, locate the listed parameter, where the related binary code can be executed:

   File Format	Parameter	Setting to Add
   Snappy	"data-service.jvmOptions"	-Dorg.xerial.snappy.tempdir=<some executable directory>
   TDE	"batch-job-runner.jvmOptions"	-Djna.tmpdir=<some executable directory>

4. Save your changes and restart the platform.

5. Run a job configured for direct publication of the modified file format.