Valid Compression Types for Parquet Format on Hadoop

Compression Types for Parquet Format

Question

You are writing some data on Hadoop in the parquet format using spark.

You need to enable compression.

Which of the following is/are the valid compression type(s) that you can use for parquet format?

Answers

Explanations

Click on the arrows to vote for the correct answer

A. B. C. D. E.

Correct Answer: E

In Spark 2.1, the supported compression types of Parquet data types are: none, gzip, snappy and lzo.

For Spark 2.4 / 3.0, the supported compression types are: uncompressed, none, snappy,lzo, gzip, brotli, lz4, and zstd.

Option A is incorrect.

none is not the only supported compression format.

The complete Parquet dataset supports all given compression types.

Option B is incorrect.

gzip is not the only supported compression format.

The complete Parquet dataset supports all given compression types.

Option C is incorrect.

snappy is not the only supported compression format.

The complete Parquet dataset supports all given compression types.

Option D is incorrect.

lzo is not the only supported compression format.

The complete Parquet dataset supports all given compression types.

Option E is correct.

The Parquet dataset supports all given compression types.

To know more about parquet format in Azure Data Factory, please visit the below-given link:

When writing data in Parquet format using Spark, you can enable compression to reduce the size of the data stored on disk. The supported compression codecs for Parquet format include:

  • Gzip: Gzip is a widely used compression format that compresses the data in a single file. Gzip is a good option if you need high compression ratios and don't care about the decompression speed.

  • Snappy: Snappy is a fast, efficient compression codec that can achieve high compression ratios with very little overhead. Snappy compression is a good choice if you need fast compression and decompression speeds with reasonable compression ratios.

  • LZO: LZO is a high-performance, lossless compression codec that is optimized for Hadoop workloads. LZO provides good compression ratios and fast compression and decompression speeds.

  • None: If you don't need compression, you can write the data in uncompressed format by specifying "none" as the compression codec.

So, the correct answer to the question is E. All of these, as all the options are valid compression types that can be used for Parquet format.