spark.sql vs SqlContext

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spark.sql vs SqlContext



I have used SQL in Spark, in this example:


results = spark.sql("select * from ventas")



where ventas is a dataframe, previosuly cataloged like a table:


df.createOrReplaceTempView('ventas')



but I have seen other ways of working with SQL in Spark, using the class SqlContext:


df = sqlContext.sql("SELECT * FROM table")



What is the difference between both of them?



Thanks in advance




2 Answers
2



Sparksession is the preferred way of working with Spark object now. Both Hivecontext and SQLContext are available as a part of this single object SparkSession.



You are using the latest syntax by creating a view df.createOrReplaceTempView('ventas').



From a user's perspective (not a contributor), I can only rehash what the developer's provided in the upgrade notes:



Before 2.0, the SqlContext needed an extra call to the factory that creates it. With SparkSession, they made things a lot more convenient.


SqlContext


SparkSession



If you take a look at the source code, you'll notice that the SqlContext class is mostly marked @deprecated. Closer inspection shows that the most commonly used methods simply call sparkSession.


SqlContext


@deprecated


sparkSession



For more info, take a look at the developer notes, Jira issues, conference talks on spark 2.0, and Databricks blog.






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