Is Hive required for Spark?

Can Spark SQL run without hive?

1 Answer. If spark is used to execute simple sql queries or not connected with hive metastore server, its uses embedded derby database and a new folder with name metastore_db will be created under the user home folder who executes the query.

Does Spark SQL use hive?

Hive comes bundled with the Spark library as HiveContext, which inherits from SQLContext. Using HiveContext, you can create and find tables in the HiveMetaStore and write queries on it using HiveQL.

Do I need to install Hadoop for Spark?

As per Spark documentation, Spark can run without Hadoop. You may run it as a Standalone mode without any resource manager. But if you want to run in multi-node setup, you need a resource manager like YARN or Mesos and a distributed file system like HDFS,S3 etc. Yes, spark can run without hadoop.

What is difference between hive and Spark?

Usage: – Hive is a distributed data warehouse platform which can store the data in form of tables like relational databases whereas Spark is an analytical platform which is used to perform complex data analytics on big data.

Why do we need hive?

Hive allows users to read, write, and manage petabytes of data using SQL. Hive is built on top of Apache Hadoop, which is an open-source framework used to efficiently store and process large datasets. As a result, Hive is closely integrated with Hadoop, and is designed to work quickly on petabytes of data.

How do I run a SQL script in spark?

Here we go!

  1. Create SparkConf to set Application name and execution mode.
  2. Instantiate Spark context "sc", this is the crux of scala /spark program.
  3. Create sql context using "sc", it is used to run queries.
  4. Import sql packages for implicit conversions and other functionalities.
  5. Create rdd on Input Data.

How do I enable hive support in spark?

to connect to hive metastore you need to copy the hive-site. xml file into spark/conf directory. After that spark will be able to connect to hive metastore.

How do I run hive query on Spark?

Procedure

  1. Start the Spark shell. bin/dse spark.
  2. Use the provided HiveContext instance sqlContext to create a new query in HiveQL by calling the sql method on the sqlContext object.. scala> val results = sqlContext.sql("SELECT * FROM my_keyspace.my_table")

23-Sept-2021

Can I learn Spark without Hadoop?

No, you don't need to learn Hadoop to learn Spark. Spark was an independent project . But after YARN and Hadoop 2.0, Spark became popular because Spark can run on top of HDFS along with other Hadoop components. … Hadoop is a framework in which you write MapReduce job by inheriting Java classes.

Can hive work without Hadoop?

5 Answers. To be precise, it means running Hive without HDFS from a hadoop cluster, it still need jars from hadoop-core in CLASSPATH so that hive server/cli/services can be started. btw, hive.

Which is better Spark or Hive?

Hive and Spark are both immensely popular tools in the big data world. Hive is the best option for performing data analytics on large volumes of data using SQLs. Spark, on the other hand, is the best option for running big data analytics. It provides a faster, more modern alternative to MapReduce.

Why Hive when we have Spark SQL?

Hive provides schema flexibility, portioning and bucketing the tables whereas Spark SQL performs SQL querying it is only possible to read data from existing Hive installation. Hive provides access rights for users, roles as well as groups whereas no facility to provide access rights to a user is provided by Spark SQL.

What is Hive on Spark?

Hive on Spark provides Hive with the ability to utilize Apache Spark as its execution engine. set hive. execution. engine=spark; Hive on Spark was added in HIVE-7292.

What SQL dialect does spark use?

For a SQLContext, the only dialect available is “sql” which uses a simple SQL parser provided by Spark SQL. In a HiveContext, the default is “hiveql”, though “sql” is also available.

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