Getting Started with GemFire XD provides step-by-step
procedures for installing, configuring, and using GemFire XD. The
guide also explains main concepts and provides tutorials to help you quickly
begin using GemFire XD.
GemFire XD in 15 Minutes
Need a quick introduction to GemFire XD? Take this 15-minute tour to try out the basic features and functionality.
Overview of Pivotal GemFire XD
Pivotal GemFire XD is a memory-optimized, distributed data store that is designed for applications that have demanding scalability and availability requirements. With GemFire XD you can manage data entirely using in-memory tables, or you can persist very large tables to local disk store files or to a Hadoop Distributed File System (HDFS) for big data deployments. In this initial release, GemFire XD provides a low-latency SQL interface to in-memory table data, while seamlessly integrating data that is persisted in HDFS. A single GemFire XD distributed system can be easily scaled out using commodity hardware to support thousands of concurrent clients, and you can also replicate data between distinct GemFire XD clusters over a WAN interface. GemFire XD also provides easy access to persisted HDFS data using tools in the Pivotal HD ecosystem such as MapReduce or HAWQ (using the GemFire XD PXF driver that is installed with HAWQ).
Installing GemFire XD
You install GemFire XD from a downloaded RPM file (RHEL only), as a component of Pivotal HD Enterprise. GemFire XD requires Pivotal HD Enterprise for all Hadoop integration features. Pivotal HD Enterprise is a commercially-supported distribution of the Apache Hadoop stack including HDFS, MapReduce, Hive, Mahout, Pig, HBase, Yarn, Zookeeper, Sqoop and Flume packages from The Apache Foundation.
Connecting to GemFire XD with JDBC Tools
Third-party JDBC tools can help you browse data in tables, issue SQL commands, design new tables, and so forth. You can configure these tools to use the GemFire XD JDBC thin client driver to connect to a GemFire XD distributed system.
Learn to configure and use GemFire XD features such as table replication and partitioning, persisting data to local disk stores and HDFS, and dynamically resizing the cluster.
When you persist the data for a GemFire XD table to HDFS, the HDFS log files enable you to analyze the table data outside of the GemFire XD distributed system, using Hadoop tools such as MapReduce or Pivotal HAWQ. GemFire XD includes a MapReduce example that helps you generate HDFS table data and then access the data using a Hadoop MapReduce job.