SysTools Parquet Splitter Software

The SysTools Parquet Splitter Software is a robust solution that allows users to effectively split large .parquet files to multiple smaller and more manageable files. With the help of this utility, users can effortlessly break .parquet files based on size, number of records, and based on specified columns. Handling large .parquet files is often a complex task, however, this smart utility allows users to carry out the entire split process in a secure and quick way.

The advanced Parquet Splitter Software is helpful for data analysts and developers who work on big data platforms such as Apache Spark, Hadoop, etc. This utility allows users to split Parquet files easily, further improving performance, data sharing, and minimizing the issues caused due to large and unmanageable .parquet files.

Prominent Features of SysTools Parquet Splitter Software

Effective Parquet File Split

This effective utility to split .parquet files allows users to split Parquet file into smaller chunks in a quick and hassle-free way. The Parquet split tool helps users break large files into more manageable files efficient for sharing and analysis. The utility also ensures no data is affected or compromised during the split process.

Supports Multiple File Split at Once

The Parquet Splitter Software offers dual modes to add .parquet files in the software. The Add Files mode helps with adding individual files for the split process. Whereas, the Add Folder option allows users to add a complete folder for convenient split process.

Split by Size, Records, and Columns

This advanced utility has many notable features, one of them being the split modes provided. The tool offers three split by modes, i.e., Split by Records, Split by Size, and Split by Columns. With the help of these modes, users can split the files as per their requirement.

Easily Split Nested Parquet Files

The Parquet File Splitter is designed by experts and is capable of splitting nested .parquet file structures without compromising the data. The tool preserves nested fields, complex column structures, and arrays during the split parquet file into smaller chunks process.

Maintains File Hierarchy Throughout

It is an advanced utility for splitting large Parquet files easily without affecting the data structure. The Parquet Splitter Software preserves the database structure, schema, data types, and metadata during and after the process is completed.

Save Resultant Files at Desired Location

This Parquet Split utility allows users to choose the destination folder of their choice to save the resultant split files. Users can browse any location as per their desire and in case they forget to add the destination, the utility itself saves the resultant files on desktop as the default location.

Provides Split Status Report for Analysis

After the process is completed, the tool also offers a complete Split Status Report for future analysis. The report contains records for Total File Count, Success File Count, and Failed File Count. These records help users to understand whether the split process was successful or not.

Supports All Parquet Versions

The Parquet Splitter Software offers support to all .parquet file versions. The tool can efficiently split the .parquet files of v1.x and v2.x versions. Also, users can split Parquet files generated by various platforms like Apache Spark, AWS Athena, Hive, Hadoop, etc.

Fully Compatible with Windows and Mac OS

Users do not have to worry about installing the tool on a specific operating system. They can easily install and split large .parquet files with this utility on both Mac and Windows devices.

Why Choose SysTools Parquet Splitter Software?

• Offers complete precision for split Parquet file process.

• Supports nested .parquet structures for split with complete data accuracy.

• Allows users to split Parquet by size, number of records, and specified columns.

• Fully compatible with Windows and Mac OS allowing efficient Parquet file split.

• Provides support to all .parquet versions and files generated from various platforms.