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

D s product
rtrue

Info

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
rtrue
 can read and import directly these file formats:

  • Excel (XLS/XLSX), upload only

    Tip

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

  • CSV
  • JSON, including nested

    Info

    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
  • XML

    Info

    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

Info

NOTE:

D s product
supports Hive connectivity, which can be used to read data for Hadoop file formats that are not listed here, such as Parquet. For more information, please view the documentation for your Hive version.

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)
  • Avro

    Info

    NOTE: The Photon and Spark running environments apply Snappy compression to this format.

  • Parquet

    Info

    NOTE: The Photon and Spark running environments apply Snappy compression to this format.

Compression Algorithms:

 

 

Info

NOTE: Importing a compressed file with a high compression ratio can overload the available memory for the application. In such cases, you can uncompress the file before uploading.

Or, if that fails, you should contact your administrator about increasing the Java Heap Size memory.
Info

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:

 GZIPBZIPSnappy
CSV SupportedSupportedSupported
JSONSupportedSupportedSupported
Avro  Supported
Hive  Supported

Write Native File Formats:

 GZIPBZIPSnappy
CSVSupportedSupportedSupported
JSONSupportedSupportedSupported
Avro  Supported; always on
Hive  Supported; always on