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How to Read MySQL Tables as Spark DataFrames?

Patricia Arquette
Release: 2024-11-01 02:08:02
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How to Read MySQL Tables as Spark DataFrames?

Integrating Apache Spark with MySQL for Database Table Reading

To connect Apache Spark with MySQL and leverage database tables as Spark dataframes, follow these steps:

  1. Create a Spark Session:

    <code class="python">from pyspark.sql import SparkSession
    
    # Create a Spark session object
    spark = SparkSession.builder \
        .appName("Spark-MySQL-Integration") \
        .getOrCreate()</code>
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  2. Instantiate a MySQL Connector:

    <code class="python">from pyspark.sql import DataFrameReader
    
    # Create a DataFrameReader object for MySQL connection
    jdbc_df_reader = DataFrameReader(spark)</code>
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  3. Configure MySQL Connection Parameters:

    <code class="python"># Set MySQL connection parameters
    jdbc_params = {
        "url": "jdbc:mysql://localhost:3306/my_db",
        "driver": "com.mysql.jdbc.Driver",
        "dbtable": "my_table",
        "user": "root",
        "password": "password"
    }</code>
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  4. Read Database Table:

    <code class="python"># Read the MySQL table as a Spark dataframe
    dataframe_mysql = jdbc_df_reader.format("jdbc") \
        .options(**jdbc_params) \
        .load()
    
    # Print the dataframe schema
    dataframe_mysql.printSchema()</code>
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This approach demonstrates how to integrate Apache Spark with MySQL, allowing you to access database tables as Spark dataframes.

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