Parquet is an open source file format by Apache for the Hadoop infrastructure. Well, it started as a file format for Hadoop, but it has since become very popular and even cloud service providers such as AWS have started supporting the file format. This could only mean that Parquet should be doing something right. In this post, we’ll see what exactly is the Parquet file format, and then we’ll see a simple Java example to create or write Parquet files.
Intro to Parquet File Format
We store data as rows in the traditional approach. But Parquet takes a different approach, where it flattens the data into columns before storing it. This allows for better data compression for storing, and also for better query performance. Also, because of this storage approach, the format can handle data sets with large number of columns.
Most big data projects use the Parquet file format because of all these features. Parquet files also reduce the amount of storage space required. In most cases, we use queries with certain columns. The beauty of the file format is that the data for a column is all adjacent, so the queries run faster.
Because of the optimization and the popularity of the file format, even Amazon provides built-in features to transform incoming streams of data into Parquet files before saving into S3 (which acts as a data lake). I have used this extensively with Amazon’s’Athena and some Apache services. For more information about the Parquet file system, you can refer the official documentation.
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