How to check if a DataFrame was already cached/persisted before?

问题

For spark's RDD object this is quite trivial as it exposes a getStorageLevel method, but DF does not seem to expose anything similar. anyone?

回答1:

You can check weather a DataFrame is cached or not using Catalog (org.apache.spark.sql.catalog.Catalog) which comes in Spark 2.

Code example :

  val sparkSession = SparkSession.builder.
      master("local")
      .appName("example")
      .getOrCreate()

    val df = sparkSession.read.csv("src/main/resources/sales.csv")
    df.createTempView("sales")

    //interacting with catalog

    val catalog = sparkSession.catalog

    //print the databases

    catalog.listDatabases().select("name").show()

    // print all the tables

    catalog.listTables().select("name").show()

    // is cached
    println(catalog.isCached("sales"))
    df.cache()
    println(catalog.isCached("sales"))

Using the above code you can list all the tables and check weather a table is cached or not.

You can check the working code example here

来源：https://stackoverflow.com/questions/41238986/how-to-check-if-a-dataframe-was-already-cached-persisted-before