Supported File Formats
This section contains information on the fie formats and compression schemes that are supported for input to and output of the Dataprep by Trifacta platform.
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 Trifacta Application identifies file formats based on the extension of the filename. If no extension is provided, the Trifacta Application 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.
File path length limits
Maximum character limits for file paths:
File paths to sources for imported datasets:
1024Tip
This limit (
storagelocations) applies to both files and tables.File paths to output files:
2048Tip
This limit (
writesettings) applies to files stored on any file-based storage location.
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:
"{", "*", "\"
Dataflow running environment:
@
Native Input File Formats
The Dataprep by Trifacta platform 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 Trifacta Application 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
The Dataprep by Trifacta platform 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.
Plain Text
LOG
TSV
Parquet
Note
When working with datasets sourced from Parquet files, lineage information and the
$sourcerownumberreference are not supported.
Avro
Note
When working with datasets sourced from Avro files, lineage information and the
$sourcerownumberreference are not supported.Google Sheets
Note
This feature may not be available in all product editions. For more information on available features, see Compare Editions.
Note
Individual users must enable access to their Google Drive. No data other than Google Sheets is read from Google Drive.
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. If you are encountering issues, try to Save As to XLS or XLSX from within the Microsoft Excel application.
Tip
You may import multiple worksheets from a single workbook at one time.
Google Sheets
Note
This feature may not be available in all product editions. For more information on available features, see Compare Editions.
Tip
You may import multiple sheets from a single Google Sheet at one time.
PDF
JSON
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.
Parsing Limits
After a file is passed into the Trifacta Application, a set of transformations is applied to it to prepare it for use in the application. These transformations may impose additional limits on the file that is imported. When these transformations fail, the file may be imported into the application as a single column of data. For more information, see Initial Parsing Steps.
Native Output File Formats
Dataprep by Trifacta can write to these file formats:
Note
Some output formats may need to be enabled by an administrator.
CSV
JSON
Avro
Note
The Trifacta Photon and Spark running environments apply Snappy compression to this format.
BigQuery Table
Compression Algorithms
When a file is imported, the Trifacta Application 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.
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 |
Write Native File Formats
GZIP | BZIP | Snappy | |
CSV | Supported | Supported | Not supported |
JSON | Supported | Supported | Not supported |
Snappy compression formats
Dataprep by Trifacta 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 |