Parquet Partition

What is Parquet Partition?

In Apache Parquet, partitioning is the process of dividing a large dataset into smaller, more manageable subsets based on the values of one or more columns. The partition key is the column or columns used to define the partitions.

To use partitioning in Parquet, you first need to define the partition schema, which specifies the column or columns to be used as the partition key. How to choose the right partition key will be discussed later in this blog.

Once the partition schema is defined, you can write data to the Parquet file and specify the partition key values for each record. For example, if you are partitioning by date, you might write records to the file like this:

date=2022–01–01
date=2022–01–02
date=2022–01–03
date=2022–01–04

This would result in the data being stored in two partitions, one for January 1, 2022 and one for January 2, 2022.

To query the data, you can use the partition key as a filter, like this:

SELECT * FROM mytable WHERE date=’2022–01–01'

This will only return the records from the January 1, 2022 partition, making the query more efficient than if it had to scan the entire dataset. In Apache Parquet, partitioning is the process of dividing a large dataset into smaller, more manageable subsets based on the values of one or more columns. The partition key is the column or columns used to define the partitions.