Supported applications for MapReduce

Apache Hadoop
Apache Hadoop is a distributed computing platform that primarily consists of the Hadoop Distributed File System (HDFS) and an implementation of the MapReduce programming paradigm.
Apache Hadoop with Linux on POWER
Linux® distributions which are supported on IBM Spectrum Symphony are also supported on Linux on POWER®systems.
IBM Spectrum Scale file placement optimizer
The IBM Spectrum Scale is a high-performance cluster file system, providing concurrent access to one or more file systems from multiple nodes. Within IBM Spectrum Scale, the File Placement Optimizer (FPO) feature provides a flexible file system that can be deployed as an alternative to HDFS, bringing full Portable Operating System Interface (POSIX) file system compliance, no single point of failure, and enhanced security. FPO is available with IBM Spectrum Scale on Linux. Follow these steps to install IBM Spectrum Scale and run MapReduce jobs in your IBM Spectrum Scale FPO cluster.
Cloudera's distribution including Apache Hadoop
The MapReduce framework in IBM Spectrum Symphony can work with Cloudera's Distribution including Apache Hadoop (CDH). The MapReduce cluster can run in addition to a Cloudera HDFS to provide improved performance, high availability, robust framework, and the ability to reuse existing data in the Cloudera HDFS. Optionally, you can activate high availability (HA) within the MapReduce framework to automate a failover process for all HDFS daemons on all nodes (NameNode, Secondary NameNode, and DataNodes).
Appistry CloudIQ Storage
Appistry CloudIQ Storage is a distributed file system that enables computational storage. Computational storage unifies applications and data by storing data across commodity servers and migrating application processing to the machines containing the relevant data.
Hortonworks Data Platform as a distributed file system
Hortonworks Data Platform (HDP) is an open-source platform for storing, processing, and analyzing large volumes of data. It supports various Apache Hadoop projects, including the Hadoop Distributed File System (HDFS), MapReduce, Apache Pig, and Apache Mahout.
Hortonworks Data Platform MapReduce and YARN
Follow these steps to integrate the IBM Spectrum Symphony MapReduce and YARN engine with Hortonworks Data Platform (HDP) 2.3.
MapR
The MapReduce framework IBM Spectrum Symphony can work with MapR, an enterprise distribution of Apache Hadoop.
TeraSort benchmark
The TeraSort benchmark suite sorts data as fast as possible to benchmark the performance of the MapReduce framework in IBM Spectrum Symphony. TeraSort combines testing the HDFS and MapReduce layers of a Hadoop cluster and consists of three MapReduce programs.
HiBench benchmark
The HiBench benchmark suite consists of a set of Hadoop programs that help evaluate the Hadoop framework in terms of speed, throughput, HDFS bandwidth, system resource utilizations, and data access patterns.
Apache Pig
Apache Pig is a platform for analyzing large data sets and consists of a high-level language for use in data analysis programs and is coupled with the MapReduce infrastructure for evaluating these programs. Pig provides a script language, Pig Latin, which can be compiled to a MapReduce program by Pig. As a result, using Pig can reduce the time to develop new MapReduce applications.
Apache Mahout
Apache Mahout is an open source project to create scalable, machine learning algorithms. Mahout operates in addition to Hadoop, which allows you to apply the concept of machine learning via a selection of Mahout algorithms to distributed computing via Hadoop. Mahout's core algorithms include recommendation mining, clustering, classification, and frequent item-set mining.
Apache HBase
Apache HBase is an open-source, distributed, column-oriented store. HBase is the Hadoop database and provides Bigtable-like capabilities in addition to Hadoop and HDFS.
Apache Oozie
Apache Oozie is an open-source workflow and coordination service to manage data processing jobs for Hadoop. It is an extensible, scalable, and data-aware service to orchestrate dependencies between jobs running on Hadoop (including HDFS, Pig, and MapReduce).
Apache Zookeeper
Apache Zookeeper is an open-source project providing a centralized configuration service and naming registry for large distributed systems. In essence, Zookeeper is a service layer on your cluster that serves as a single point of management for distributed applications, enabling you to streamline application management. Note, however, that Zookeeper is meant for use by application developers, rather than by administrators.
Apache Hive
Apache Hive is a data warehouse system that summarizes data, facilitates ad-hoc queries, and analyzes large data sets stored in Hadoop-compatible file systems. It provides a mechanism to project structure on this data and to query data using a SQL-like language called HiveQL. This language also allows you to plug in custom mappers and reducers when it is inconvenient or inefficient to express logic in HiveQL.
Hadoop Pipes
Apache Hadoop provides an adapter layer called pipes which allows C++ application code to be used in MapReduce programs. Applications that require high numerical performance may see better throughput if written in C++ and used through Pipes.
Datameer
Datameer Analytics Solution (DAS) is a Hadoop-based solution for big data analytics that includes data source integration, storage, an analytics engine and visualization.
Mixed data source
The Mixed Data Source example consists of two MapReduce applications that have different data sources and destinations for input and output running within the MapReduce framework in IBM Spectrum Symphony.

Parent topic: Integrating MapReduce applications with IBM Spectrum Symphony