Parquet Output
The Parquet Output step allows you to map PDI fields to fields within data files and choose where you want to process those files, such as on HDFS. For big data users, Parquet Input and Parquet Output steps enable you to gather data from various sources and move that data into the Hadoop ecosystem in the Parquet format.
Before you begin
Before using the Parquet Output step, you must configure a named connection for your distribution, even if your Location is set to Local. For more information, see Connecting to a Hadoop cluster with the PDI client.
General tab
Enter the following information in the transformation step fields:
Step name
Specify the unique name of the Parquet Output step on the canvas. You can customize the name or leave it as the default.
Folder/File name
Specify the location and name of the file or folder. Click Browse to display the Open dialog box and navigate to the destination file or folder. For the supported file system types, see Connecting to Virtual File Systems. When running on the Pentaho engine, a single Parquet file is created.
Overwrite existing output file
Select to overwrite an existing file that has the same file name and extension.
Fields tab
In the Fields tab, you can define properties for the fields being exported.
Parquet path
Specify the name of the column in the Parquet file.
Name
Specify the name of the PDI field.
Parquet type
Specify the data type used to store the data in the Parquet file.
Precision
Specify the total number of significant digits in the number. Applies only to the Decimal Parquet type. The default is 20.
Scale
Specify the number of digits after the decimal point. Applies only to the Decimal Parquet type. The default is 10.
Default value
Specify the default value of the field if it is null or empty.
Null
Specify whether the field can contain null values.
To help prevent a transformation failure, enter a value in Default value for every field where Null is set to No.
You can define the fields manually, or you can click Get Fields to populate the fields.
When the fields are retrieved, a PDI type is converted into an appropriate Parquet type. You can change the Parquet type by using the Type drop-down list or by entering the type manually.
InetAddress
UTF8
String
UTF8
TimeStamp
TimestampMillis
Binary
Binary
BigNumber
Decimal
Boolean
Boolean
Date
Date
Integer
Int64
Number
Double
Options tab
In the Options tab, you can define properties for the file output.
Compression
Specify the codec to use to compress the Parquet output file:
None: No compression is used. (Default)
Snappy: Uses Google’s Snappy compression library.
GZIP: Uses a compression format based on the Deflate algorithm.
Version
Specify the version of Parquet to use:
Parquet 1.0
Parquet 2.0
Row group size (MB)
Specify the group size for the rows. The default value is 0.
Data page size (KB)
Specify the page size for the data. The default value is 0.
Dictionary encoding
Specify dictionary encoding, which builds a dictionary of values encountered in a column. The dictionary page is written first, before the data pages of the column.
If the dictionary grows larger than Page size, whether in size or number of distinct values, the encoding method reverts to the plain encoding type.
Page size (KB)
Specify the page size when using dictionary encoding. The default value is 1024.
Extension
Select the extension for your output file. The default value is parquet.
Include date in file name
Add the system date to the filename in yyyyMMdd format (for example, 20181231).
Include time in file name
Add the system time to the filename in HHmmss format (for example, 235959).
Specify date time format
Select to specify the date and time format by using the drop-down list.
Metadata injection support
All fields of this step support metadata injection. You can use this step with ETL metadata injection to pass metadata to your transformation at runtime.
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