scala - Read all Parquet files saved in a folder via Spark

Scala - Read all Parquet files saved in a folder via Spark

You can read all Parquet files saved in a folder using Spark by using the spark.read.parquet method and providing the path to the folder containing the Parquet files. Here's how you can do it:

import org.apache.spark.sql.{SparkSession, DataFrame} object ReadParquetFiles { def main(args: Array[String]): Unit = { val spark = SparkSession.builder() .appName("ReadParquetFiles") .master("local[*]") .getOrCreate() val folderPath = "/path/to/parquet/folder" val parquetDF = readParquetFiles(spark, folderPath) parquetDF.show() spark.stop() } def readParquetFiles(spark: SparkSession, folderPath: String): DataFrame = { spark.read.parquet(folderPath) } }

In this code:

  • We create a SparkSession.
  • We define the folder path where the Parquet files are saved.
  • We call the readParquetFiles function, passing the SparkSession and folder path as arguments.
  • Inside the readParquetFiles function, we use the spark.read.parquet method to read all Parquet files from the specified folder.
  • Finally, we display the DataFrame containing the data from the Parquet files using the show method, and stop the SparkSession.

Make sure to replace "/path/to/parquet/folder" with the actual path to your folder containing the Parquet files.

Examples

  1. "Scala read all Parquet files in folder Spark example"

    • Description: Users might search for examples demonstrating how to read all Parquet files saved in a folder using Spark in Scala.
    • Code:
      import org.apache.spark.sql.{SparkSession, DataFrame} // Initialize SparkSession val spark = SparkSession.builder() .appName("Read Parquet Files") .getOrCreate() // Specify the folder path containing Parquet files val folderPath = "/path/to/parquet/files" // Read all Parquet files in the folder as a DataFrame val df: DataFrame = spark.read.parquet(folderPath)

  2. "Scala Spark read multiple Parquet files from folder"

    • Description: Users may want to know how to use Spark in Scala to read multiple Parquet files stored in a folder.
    • Code:
      import org.apache.spark.sql.{SparkSession, DataFrame} // Initialize SparkSession val spark = SparkSession.builder() .appName("Read Parquet Files") .getOrCreate() // Specify the folder path containing Parquet files val folderPath = "/path/to/parquet/files" // Read all Parquet files in the folder as a DataFrame val df: DataFrame = spark.read.parquet(folderPath)

  3. "Scala read all Parquet files from directory using Spark"

    • Description: This query indicates users' interest in reading all Parquet files within a directory using Spark in Scala.
    • Code:
      import org.apache.spark.sql.{SparkSession, DataFrame} // Initialize SparkSession val spark = SparkSession.builder() .appName("Read Parquet Files") .getOrCreate() // Specify the folder path containing Parquet files val folderPath = "/path/to/parquet/files" // Read all Parquet files in the folder as a DataFrame val df: DataFrame = spark.read.parquet(folderPath)

  4. "Scala Spark load all Parquet files in folder"

    • Description: Users might want to load all Parquet files located in a folder using Spark in Scala for further analysis or processing.
    • Code:
      import org.apache.spark.sql.{SparkSession, DataFrame} // Initialize SparkSession val spark = SparkSession.builder() .appName("Read Parquet Files") .getOrCreate() // Specify the folder path containing Parquet files val folderPath = "/path/to/parquet/files" // Read all Parquet files in the folder as a DataFrame val df: DataFrame = spark.read.parquet(folderPath)

  5. "Scala Spark read Parquet files from directory"

    • Description: This query indicates users' interest in reading Parquet files stored within a directory using Spark in Scala.
    • Code:
      import org.apache.spark.sql.{SparkSession, DataFrame} // Initialize SparkSession val spark = SparkSession.builder() .appName("Read Parquet Files") .getOrCreate() // Specify the folder path containing Parquet files val folderPath = "/path/to/parquet/files" // Read all Parquet files in the folder as a DataFrame val df: DataFrame = spark.read.parquet(folderPath)

  6. "Scala Spark read Parquet files in directory example"

    • Description: Users might seek examples illustrating how to read Parquet files stored in a directory using Spark in Scala.
    • Code:
      import org.apache.spark.sql.{SparkSession, DataFrame} // Initialize SparkSession val spark = SparkSession.builder() .appName("Read Parquet Files") .getOrCreate() // Specify the folder path containing Parquet files val folderPath = "/path/to/parquet/files" // Read all Parquet files in the folder as a DataFrame val df: DataFrame = spark.read.parquet(folderPath)

  7. "Scala read all Parquet files in directory Spark"

    • Description: Users may look for ways to read all Parquet files stored in a directory using Spark in Scala for data processing tasks.
    • Code:
      import org.apache.spark.sql.{SparkSession, DataFrame} // Initialize SparkSession val spark = SparkSession.builder() .appName("Read Parquet Files") .getOrCreate() // Specify the folder path containing Parquet files val folderPath = "/path/to/parquet/files" // Read all Parquet files in the folder as a DataFrame val df: DataFrame = spark.read.parquet(folderPath)

  8. "Scala Spark read Parquet files from directory recursive"

    • Description: Users might want to recursively read Parquet files from a directory and its subdirectories using Spark in Scala.
    • Code:
      import org.apache.spark.sql.{SparkSession, DataFrame} // Initialize SparkSession val spark = SparkSession.builder() .appName("Read Parquet Files") .getOrCreate() // Specify the folder path containing Parquet files val folderPath = "/path/to/parquet/files" // Read all Parquet files in the folder and its subdirectories as a DataFrame val df: DataFrame = spark.read.option("recursiveFileLookup", "true").parquet(folderPath)

  9. "Scala read all Parquet files in directory SparkSession"

    • Description: This query indicates users' interest in using SparkSession to read all Parquet files stored in a directory in Scala.
    • Code:
      import org.apache.spark.sql.{SparkSession, DataFrame} // Initialize SparkSession val spark = SparkSession.builder() .appName("Read Parquet Files") .getOrCreate() // Specify the folder path containing Parquet files val folderPath = "/path/to/parquet/files" // Read all Parquet files in the folder as a DataFrame val df: DataFrame = spark.read.parquet(folderPath)

  10. "Scala Spark read Parquet files from directory recursively"

    • Description: Users might search for methods to read Parquet files from a directory and its subdirectories recursively using Spark in Scala.
    • Code:
      import org.apache.spark.sql.{SparkSession, DataFrame} // Initialize SparkSession val spark = SparkSession.builder() .appName("Read Parquet Files") .getOrCreate() // Specify the folder path containing Parquet files val folderPath = "/path/to/parquet/files" // Read all Parquet files in the folder and its subdirectories as a DataFrame val df: DataFrame = spark.read.option("recursiveFileLookup", "true").parquet(folderPath)

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