What is Spark SQL used for?

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What is Spark SQL used for?

Spark SQL is a Spark module for structured data processing. It provides a programming abstraction called DataFrames and can also act as a distributed SQL query engine. It enables unmodified Hadoop Hive queries to run up to 100x faster on existing deployments and data.

What does Spark actually do?

Spark is a general-purpose distributed data processing engine that is suitable for use in a wide range of circumstances. On top of the Spark core data processing engine, there are libraries for SQL, machine learning, graph computation, and stream processing, which can be used together in an application.

Is Spark and PySpark same?

PySpark is the collaboration of Apache Spark and Python. Apache Spark is an open-source cluster-computing framework, built around speed, ease of use, and streaming analytics whereas Python is a general-purpose, high-level programming language.

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Is spark SQL faster than SQL?

Extrapolating the average I/O rate across the duration of the tests (Big SQL is 3.2x faster than Spark SQL), then Spark SQL actually reads almost 12x more data than Big SQL, and writes 30x more data.

Why Spark is lazy evaluation?

As the name itself indicates its definition, lazy evaluation in Spark means that the execution will not start until an action is triggered. Since transformations are lazy in nature, so we can execute operation any time by calling an action on data. Hence, in lazy evaluation data is not loaded until it is necessary.

Who created spark?

Matei Zaharia
Apache Spark, which is a fast general engine for Big Data processing, is one the hottest Big Data technologies in 2015. It was created by Matei Zaharia, a brilliant young researcher, when he was a graduate student at UC Berkeley around 2009.

What is a PySpark job?

Support multiple functions in a single script and run these functions either in sequence (similar to a pipeline) or individually. Handle arguments passed through spark-submit. Support run time tracking (crude implementation)

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How do you use CoGroup in spark?

In Spark, the cogroup function performs on different datasets, let’s say, (K, V) and (K, W) and returns a dataset of (K, (Iterable, Iterable )) tuples. This operation is also known as groupWith. In this example, we perform the groupWith operation.

What is a join query in spark?

A query that accesses in such a way is called a join query. It is quite common to join multiple data sets.The join function joins any two SparkR DataFrames based on the given join expression. In a case where no join expression is mentioned, it will perform a Cartesian join import org.apache.spark._ import org.apache.spark.sql._

Where can I find the API docs for Apache Spark?

Spark docs is: http://spark.apache.org/docs/latest/api/scala/index.html#org.apache.spark.rdd.PairRDDFunctions Thanks for contributing an answer to Stack Overflow! Please be sure to answer the question. Provide details and share your research! But avoid … Asking for help, clarification, or responding to other answers.