Parquet is a columnar format file supported by many other data processing systems. Spark SQL performs both read and write operations with Parquet file and consider it be one of the best big data analytics formats so far.
Parquet is a columnar format, supported by many data processing systems. The advantages of having a columnar storage are as follows:
1. Columnar storage limits IO operations.
2. It can fetch specific columns that you need to access.
3. Columnar storage consumes less space.
4. It gives better-summarized data and follows type-specific encoding.
Posted Date:- 2021-09-25 06:19:50
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What file systems does Spark support?
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How is machine learning implemented in Spark?
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How to import third party jars or dependencies in the Databricks?
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Define Partitions in Apache Spark.
What is Executor Memory in a Spark application?
How do we create RDDs in Spark?
Is there any benefit of learning MapReduce if Spark is better than MapReduce?
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