Quick Start

This tutorial provides a quick introduction to using CarbonData.

Prerequisites

• Installation and building CarbonData.
• Create a sample.csv file using the following commands. The CSV file is required for loading data into CarbonData.

cd carbondata
cat > sample.csv << EOF
id,name,city,age
1,david,shenzhen,31
2,eason,shenzhen,27
3,jarry,wuhan,35
EOF

Interactive Analysis with Spark Shell

Version 2.1

Apache Spark Shell provides a simple way to learn the API, as well as a powerful tool to analyze data interactively. Please visit Apache Spark Documentation for more details on Spark shell.

Basics

Start Spark shell by running the following command in the Spark directory:

./bin/spark-shell --jars <carbondata assembly jar path>

In this shell, SparkSession is readily available as ‘spark’ and Spark context is readily available as ‘sc’.

In order to create a CarbonSession we will have to configure it explicitly in the following manner :

• Import the following :

import org.apache.spark.sql.SparkSession
import org.apache.spark.sql.CarbonSession._

• Create a CarbonSession :

val carbon = SparkSession.builder().config(sc.getConf).getOrCreateCarbonSession("<hdfs store path>")

NOTE: By default metastore location is pointed to “../carbon.metastore”, user can provide own metastore location to CarbonSession like SparkSession.builder().config(sc.getConf).getOrCreateCarbonSession("<hdfs store path>", "<local metastore path>")

Executing Queries

Creating a Table

scala>carbon.sql("CREATE TABLE IF NOT EXISTS test_table(id string, name string, city string, age Int) STORED BY 'carbondata'")

Loading Data to a Table

scala>carbon.sql("LOAD DATA INPATH 'sample.csv file path' INTO TABLE test_table")

NOTE:Please provide the real file path of sample.csv for the above script.

Query Data from a Table

scala>carbon.sql("SELECT * FROM test_table").show()

scala>carbon.sql("SELECT city, avg(age), sum(age) FROM test_table GROUP BY city").show()

Interactive Analysis with Spark Shell

Version 1.6

Basics

Start Spark shell by running the following command in the Spark directory:

./bin/spark-shell --jars <carbondata assembly jar path>

NOTE: In this shell, SparkContext is readily available as sc.

• In order to execute the Queries we need to import CarbonContext:

import org.apache.spark.sql.CarbonContext

• Create an instance of CarbonContext in the following manner :

val cc = new CarbonContext(sc)

NOTE: By default store location is pointed to “../carbon.store”, user can provide own store location to CarbonContext like new CarbonContext(sc, storeLocation).

Executing Queries

Creating a Table

scala>cc.sql("CREATE TABLE IF NOT EXISTS test_table (id string, name string, city string, age Int) STORED BY 'carbondata'")

To see the table created :

scala>cc.sql("SHOW TABLES").show()

Loading Data to a Table

scala>cc.sql("LOAD DATA INPATH 'sample.csv file path' INTO TABLE test_table")

NOTE:Please provide the real file path of sample.csv for the above script.

Query Data from a Table

scala>cc.sql("SELECT * FROM test_table").show()
scala>cc.sql("SELECT city, avg(age), sum(age) FROM test_table GROUP BY city").show()