Parquet

Overview

Apache Parquet is a file format designed to support fast data processing for complex data, with several notable characteristics:

1. Columnar: Unlike row-based formats such as CSV or Avro, Apache Parquet is column-oriented – meaning the values of each table column are stored next to each other, rather than those of each record:

2. Open-source: Parquet is free to use and open source under the Apache Hadoop license, and is compatible with most Hadoop data processing frameworks. To quote the project website, “Apache Parquet is… available to any project… regardless of the choice of data processing framework, data model, or programming language.”

3. Self-describing: In addition to data, a Parquet file contains metadata including schema and structure. Each file stores both the data and the standards used for accessing each record – making it easier to decouple services that write, store, and read Parquet files.

Example use case

You have a parquet file that contains your Employee information. You want to use a batch sync to pull this info into a Cinchy table and liberate your data.

tip

The Parquet source supports batch syncs.

Info tab

You can find the parameters in the Info tab below (Image 1).

Values

Parameter	Description	Example
Title	Mandatory. Input a name for your data sync	Employee Sync
Variables	Optional. Review our documentation on Variables here for more information about this field. When uploading a local file, set this to filepath.	Since we're doing a local upload, we use "@Filepath"
Permissions	Data syncs are role based access systems where you can give specific groups read, write, execute, and/or all of the above with admin access. Inputting at least an Admin Group is mandatory.

Source tab

The following table outlines the mandatory and optional parameters you will find on the Source tab.

Source Details

The following parameters will help to define your data sync source and how it functions.

:::tip Registered Applications

For information on setting up registered applications for S3 or Azure, please see the Registered Applications page.

:::

Parameter	Description	Example
(Sync) Source	Mandatory. Select your source from the drop-down menu.	Parquet
Source	Location of the source file. Supports Local upload, Amazon S3, Azure Blob Storage with various authentication methods.	Local
Row Group Size	Mandatory. Size of Parquet Row Groups. Review the documentation here for more on Row Group sizing.	The recommended disk block/row group/file size is 512 to 1024 MB on HDFS.
Path	Mandatory. Path to source file. Local upload requires Variable in Info tab.	@Filepath
Auth Type	Defines the authentication type. Supports "Access Key" and "IAM role". Additional setup is required. Read more
Test Connection	Use to verify credentials. A "Connection Successful" pop-up appears if successful.

Schema

The Schema section is where you define which source columns you want to sync in your connection. You can repeat the values for multiple columns.

Parameter	Description	Example
Name	Mandatory. The name of your column as it appears in the source.	Name
Alias	Optional. You may choose to use an alias on your column so that it has a different name in the data sync.
Data Type	Mandatory. The data type of the column values.	Text
Description	Optional. You may choose to add a description to your column.

Select Show Advanced for more options for the Schema section.

Parameter	Description	Example
Mandatory	If both Mandatory and Validated are checked on a column, then rows where the column is empty are rejected If just Mandatory is checked on a column, then all rows are synced with the execution log status of failed, and the source error of "Mandatory Rule Violation" If just Validated is checked on a column, then all rows are synced.
Validate Data	If both Mandatory and Validated are checked on a column, then rows where the column is empty are rejected If just Validated is checked on a column, then all rows are synced.
Trim Whitespace	Optional if data type = text. For Text data types, you can choose whether to trim the whitespace._

You can choose to add in a Transformation > String Replacement by inputting the following:

Parameter	Description	Example
Pattern	Mandatory if using a Transformation. The pattern for your string replacement.
Replacement	What you want to replace your pattern with.

info

Note that you can have more than one String Replacement

Filter

You have the option to add a source filter to your data sync. Please review the documentation here for more information on source filters.

Next steps

• Configure your Destination
• Define your Sync Actions.
• Add in your Post Sync Scripts, if required.
• Click Jobs > Start a Job to begin your sync.