kissys / presto

Distributed SQL query engine for big data

Presto

Presto is a distributed SQL query engine for big data.

See the User Manual for deployment instructions and end user documentation.

Requirements

• Mac OS X or Linux
• Java 7, 64-bit
• Maven 3 (for building)
• Python 2.4+ (for running with the launcher script)

Building Presto

Presto is a standard Maven project. Simply run the following command from the project root directory:

mvn clean install

On the first build, Maven will download all the dependencies from the internet and cache them in the local repository (~/.m2/repository), which can take a considerable amount of time. Subsequent builds will be faster.

Presto has a comprehensive set of unit tests that can take several minutes to run. You can disable the tests when building:

mvn clean install -DskipTests

Running Presto in your IDE

Overview

After building Presto for the first time, you can load the project into your IDE and run the server. We recommend using IntelliJ IDEA. Because Presto is a standard Maven project, you can import it into your IDE using the root pom.xml file. In IntelliJ, choose Open Project from the Quick Start box or choose Open from the File menu and select the root pom.xml file.

After opening the project in IntelliJ, double check that the Java SDK is properly configured properly for the project:

• Open the File menu and select Project Structure
• In the SDKs section, ensure that a 1.7 JDK is selected (create one if none exist)
• In the Project section, ensure the Project language level is set to 7.0 as Presto makes use of several Java 7 language features

Presto comes with sample configuration that should work out-of-the-box for development. Use the following options to create a run configuration:

• Main Class: com.facebook.presto.server.PrestoServer
• VM Options: -ea -Xmx2G -Dconfig=etc/config.properties -Dlog.levels-file=etc/log.properties
• Working directory: $MODULE_DIR$
• Use classpath of module: presto-server

The working directory should be the presto-server subdirectory. In IntelliJ, using $MODULE_DIR$ accomplishes this automatically.

Additionally, the Hive plugin must be configured with location of your Hive metastore Thrift service. Add the following to the list of VM options, replacing localhost:9083 with the correct host and port (or use the below value if you do not have a Hive metastore):

-Dhive.metastore.uri=thrift://localhost:9083

Using SOCKS for Hive or HDFS

If your Hive metastore or HDFS cluster is not directly accessible to your local machine, you can use SSH port forwarding to access it. Setup a dynamic SOCKS proxy with SSH listening on local port 1080:

ssh -v -N -D 1080 server

Then add the following to the list of VM options:

-Dhive.metastore.thrift.client.socks-proxy=localhost:1080

Using HDFS with Federation

If your Hive metastore references files stored on a federated HDFS, you should provide your HDFS config files as a VM option:

-Dhive.config.resources=/etc/hadoop/conf/core-site.xml,/etc/hadoop/conf/hdfs-site.xml

Running the CLI

Start the CLI to connect to the server and run SQL queries:

presto-cli/target/presto-cli-*-executable.jar

Run a query to see the nodes in the cluster:

SELECT * FROM sys.node;

In the sample configuration, the Hive connector is mounted in the hive catalog, so you can run the following queries to show the tables in the Hive database default:

SHOW TABLES FROM hive.default;