Read & Write Parquet file using Databrick and PySpark
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In this video I will show you how to Read & Write Parquet file using Databrick and PySpark.
Apache Parquet is an open source, column-oriented data file format designed for efficient data storage and retrieval. It provides efficient data compression and encoding schemes with enhanced performance to handle complex data in bulk. Apache Parquet is designed to be a common interchange format for both batch and interactive workloads.
=====⏱️Timestamps⏱️=====
00:00 Read & Write Parquet file using Databrick and PySpark - Intro.
01:01 What is Parquet file.
02:00 What is meant by Columnar Storage.
03:19 Advantages of Apache Parquet file.
04:00 Different between CSV and Parquet file.
06:38 Create JDBC connection to AZURE SQL Server.
11:02 Write data in DBFS as Parquet format.
13:07 Display the written Parquet file in the DBFS.
14:06 Read Parquet file data
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