Learn how to choose the right file type for storing the history of transactions executed against an Azure Synapse Analytics serverless SQL pool. Discover the benefits of using Parquet for transactional data processing and large-scale data storage. Get expert advice on data storage and processing for big data environments.
Table of Contents
Question
You have an Azure subscription that contains an Azure Synapse Analytics serverless SQL pool named Pool1.
You plan to deploy a data lake that will record the history of transactions executed against Pool1.
You need to recommend which type of file to use to store the history. The solution must ensure that the history is written in the scope of the related transaction.
Which file type should you recommend?
A. JSON
B. Avro
C. Delta
D. Parquet
Answer
D. Parquet
Explanation
Parquet is a columnar storage format that is optimized for use with Spark and other big data processing frameworks. It is designed to store large amounts of data and is optimized for query performance. Parquet supports transactional data processing and can handle complex data structures, making it a good choice for storing the history of transactions executed against Pool1.
The other options are not the best choices for storing the history of transactions:
Option A, JSON, is a flexible and lightweight data interchange format that is easy to read and write. However, it is not optimized for query performance and may not be the best choice for large-scale data storage.
Option B, Avro, is a data serialization format that is designed for Hadoop and other big data processing frameworks. While it supports transactional data processing, it may not be the best choice for storing large amounts of data.
Option C, Delta, is a data storage format that is designed for streaming data processing. While it supports transactional data processing, it may not be the best choice for storing historical data.
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