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Apache lights a fire under Hadoop with Spark

Apache lights a fire under Hadoop with Spark

Apache Spark might provide a faster alternative to Hadoop MapReduce

The Apache Software Foundation has announced the first production-ready release of Spark, analysis software that could speed jobs that run on the Hadoop data-processing platform.

Dubbed the "Hadoop Swiss Army knife," Apache Spark provides the ability to create data-analysis jobs that can run 100 times faster than those running on the standard Apache Hadoop MapReduce.

MapReduce has been widely criticized as a bottleneck in Hadoop clusters because it executes jobs in batch mode, which means that real-time analysis of data is not possible.

Spark provides an alternative to MapReduce in that it executes jobs in short bursts of micro-batches that are five seconds or less apart. It also provides more stability than real-time, stream-oriented Hadoop frameworks such as Twitter Storm.

The software can be used for a variety of jobs, such as an ongoing analysis of live data, and, thanks to a software library, more computationally in-depth jobs involving machine learning and graph processing.

Using Spark, developers can write data-analysis jobs in Java, Scala or Python, using a set of more than 80 high-level operators.

With the version 1.0 release, Apache Spark now offers a stable API (application programming interface), which developers can use to interact with Spark though their own applications.

Also new for version 1.0 is a Spark SQL component for accessing structured data, allowing the data to be interrogated alongside unstructured data in analysis work.

Apache Spark is fully compatible with Hadoop's Distributed File System (HDFS), as well as with other Hadoop components such as YARN (Yet Another Resource Negotiator) and the HBase distributed database.

The University of California, Berkeley's AMP (Algorithms, Machines and People) Lab originally developed Spark, and Apache adopted it as an incubator project in June 2013. IT companies such as Cloudera, Pivotal, IBM, Intel and MapR have all folded Spark into their Hadoop stacks. Databricks, a company founded by some of the developers of Spark, offers commercial support for the software.

Both Yahoo and NASA, among others, use the software for daily data operations.

As with all Apache software, Apache Spark has been issued under the Apache License version 2.0.

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