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Step 2: Convert Avro to Parquet

While Avro is excellent for streaming, Parquet is the industry standard for efficient analytics and data warehousing. It uses a columnar storage format that is highly optimized for analytical queries.

This step teaches you how to convert the Avro data from Step 1 into the Parquet format.

The Goal​

You will add processors to your pipeline to take the binary Avro data, convert it back to a structured JSON object, and then re-encode it into the binary Parquet format.

The "De-serialize -> Re-serialize" Pattern​

Converting between two binary formats is a two-step process:

  1. Decode Avro: Use a decoder that matches the producer schema and framing.
  2. Encode Parquet: Collect structured records into batches and use parquet_encode with explicit column types.

Implementation boundary​

This is a design pattern, not a maintained Avro-to-Parquet pipeline. See the retail Parquet reference for the maintained batching and encoding boundary. Supply and verify the Avro decoder separately; the format HTTP reference handles JSON, CSV, and XML.

Verification​

Unreadable console bytes do not verify a Parquet conversion. Decode the result with the intended schema and consumer before treating it as valid output.

This page records configuration intent, not a current executed result.