Temp table caching with spark-sql

Is a table registered with registerTempTable (createOrReplaceTempView with spark 2.+) cached?

Using Zeppelin, I register a DataFrame in my scala code, after heavy computation, and then within %pyspark I want to access it, and further filter it.

Will it use a memory-cached version of the table? Or will it be rebuilt each time?

2 Answers

Registered tables are not cached in memory.

The registerTempTable createOrReplaceTempView method will just create or replace a view of the given DataFrame with a given query plan.

It will convert the query plan to canonicalized SQL string, and store it as view text in metastore, if we need to create a permanent view.

You'll need to cache your DataFrame explicitly. e.g :

df.createOrReplaceTempView("my_table") # df.registerTempTable("my_table") for spark <2.+ spark.cacheTable("my_table") 

EDIT:

Let's illustrate this with an example :

Using cacheTable :

scala> val df = Seq(("1",2),("b",3)).toDF // df: org.apache.spark.sql.DataFrame = [_1: string, _2: int] scala> sc.getPersistentRDDs // res0: scala.collection.Map[Int,org.apache.spark.rdd.RDD[_]] = Map() scala> df.createOrReplaceTempView("my_table") scala> sc.getPersistentRDDs // res2: scala.collection.Map[Int,org.apache.spark.rdd.RDD[_]] = Map() scala> spark.catalog.cacheTable("my_table") // spark.cacheTable("...") before spark 2.0 scala> sc.getPersistentRDDs // res4: scala.collection.Map[Int,org.apache.spark.rdd.RDD[_]] = Map(2 -> In-memory table my_table MapPartitionsRDD[2] at cacheTable at <console>:26) 

Now the same example using cache.registerTempTable cache.createOrReplaceTempView :

scala> sc.getPersistentRDDs // res2: scala.collection.Map[Int,org.apache.spark.rdd.RDD[_]] = Map() scala> val df = Seq(("1",2),("b",3)).toDF // df: org.apache.spark.sql.DataFrame = [_1: string, _2: int] scala> df.createOrReplaceTempView("my_table") scala> sc.getPersistentRDDs // res4: scala.collection.Map[Int,org.apache.spark.rdd.RDD[_]] = Map() scala> df.cache.createOrReplaceTempView("my_table") scala> sc.getPersistentRDDs // res6: scala.collection.Map[Int,org.apache.spark.rdd.RDD[_]] = // Map(2 -> ConvertToUnsafe // +- LocalTableScan [_1#0,_2#1], [[1,2],[b,3]] // MapPartitionsRDD[2] at cache at <console>:28) 

It is not. You should cache explicitly:

sqlContext.cacheTable("someTable")