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

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.

Filenames

NOTE: During import, the identifies file formats based on the extension of the filename. If no extension is provided, the assumes that the submitted file is a text file of some kind. Non-text file formats, such as Avro and Parquet, require filename extensions.

NOTE: Filenames that include special characters can cause problems during import or when publishing to a file-based datastore.

Forbidden characters in import filenames:

The following list of characters present issues in the listed area of the product. If you encounter issues, the following listings may provide some guidance on where the issue occurred.

Tip: You should avoid using any of these characters in your import filenames. This list may not be complete for all available running environments.

General:
"/"
Seb browser:
"\"
Excel filenames:
"#"

Spark-based running environment:
"{", "*", "\"

Native Input File Formats

can read and import directly these file formats:

CSV

JSON v1, including nested

NOTE: JSON files can be read natively but often require additional work to properly structure into tabular format. Depending on how the is configured (v1 or v2), JSON files may require conversion before they are available for use in the application. See "Converted file formats" below.

NOTE: 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 in the User Guide

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

Avro

XML
Tip: XML files can be ingested as unstructured text.

For more information on data is handled initially, see Initial Parsing Steps in the User Guide.

Converted file formats

Files of the following type are not read into the product in their native format. Instead, these file types are converted using the Conversion Service into a file format that is natively supported, stored in the base storage layer, and then ingested for use in the product.

NOTE: Compressed files that require conversion of the underlying file format are not supported for use in the product.

Converted file formats:

Excel (XLS/XLSX)
NOTE: Other Excel-related formats, such as XLSM format, are not supported.

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

PDF
NOTE: PDF support may need to be enabled in your environment. See Import PDF Data.
- PDF is supported for import only.
- See Import PDF Data in the User Guide.

JSON v2

Notes on JSON:

There are two methods of ingesting JSON files for use in the product.

JSON v2 - This newer version reads the JSON source file through the Conversion Service, which stores a restructured version of the data in tabular format on the base storage layer for quick and simple use within the application.
Tip: This method is enabled by default and is recommended. For more information, see Working with JSON v2.
JSON v1 - This older version reads JSON files directly into the platform as text files. However, this method often requires additional work to restructure the data into tabular format. For more information, see Working with JSON v1.

Native Output File Formats

can write to these file formats:

CSV
JSON

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

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

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

Compression Algorithms

When a file is imported, the attempts to infer the compression algorithm in use based on the filename extension. For example, .gz files are assumed to be compressed with GZIP.

NOTE: Import of a compressed file whose underlying format requires conversion through the Conversion Service is not supported.

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.

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

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 in the User Guide.

Tip: If preferred, you can configure the to infer the compression scheme based on first few bytes of the file. For more information, see Miscellaneous Configuration.

Read Native File Formats

	GZIP	BZIP	Snappy	Notes
CSV	Supported	Supported	Supported
JSON v2	Not supported	Not supported	Not supported	A converted file format. See above.
JSON v1	Supported	Supported	Supported	Not a converted file format. See above.
Avro			Supported
Hive			Supported

Write Native File Formats

	GZIP	BZIP	Snappy
CSV	Supported	Supported	Supported
JSON	Supported	Supported	Supported
Avro			Supported; always on
Hive			Supported; always on

Snappy compression formats

supports the following variants of Snappy compression format:

File extension

Format name

Notes

.sz

Framing2 format

See: https://github.com/google/snappy/blob/master/framing_format.txt

.snappy

Hadoop-snappy format

See: https://code.google.com/p/hadoop-snappy/

NOTE: Xerial's snappy-java format, which is also written with a .snappy file extension by default, is not supported.

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 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 .

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:

Login to the application as an administrator.
From the menu, select User menu > Admin console > Admin settings.
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>
Hyper See previous. See previous.
Save your changes and restart the platform.
Run a job configured for direct publication of the modified file format.

File Format	Parameter	Setting to Add
Snappy	"data-service.jvmOptions"	-Dorg.xerial.snappy.tempdir=<some executable directory>
Hyper	See previous.	See previous.