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What is Spark?
Spark is a very influential open source dispensation engine that is used for Hadoop data. The analytics that are used here are quite easy to use, fast and also sophisticated. It is a data processing framework that will run parallel to Hadoop. Spark helps Hadoop to be very fast. It also makes using big data application quite easy and also combines interactive analysis, streaming and batch on all the data.
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Features and advantages of Spark
- The speed of spark is a very important feature that helps in processing big data. All organizations want their data to be analyzed as fast as possible. It is spark that makes the Hadoop applications run 100 times quicker when it runs in memory. Again with Spark, Hadoop applications are able to run 10 times faster in the disk.
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- Sparks also provides support to sophisticated analytics. It reduces operations and also supports SQL series. It also streams the data as well as the complex analytics like graph algorithms as well as machine learning. Users also have the option of combining everything together and work in a single work flow without any kind of interruption.
- Spark has the capability of running independently. It also can read all the Hadoop data and can also run on the Hadoop’s 2 YARN cluster manager. It is this feature of spark that makes it possible for you to read all hadoop data. It is again this feature that makes migration easier for Hadoop applications. However since spark uses immutability so this migration might not be possible for all scenarios in Hadoop.
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- Spark is extremely flexible as well as powerful and is best suited for interactive processing, iterative processing and also event stream processing.
- It uses the same platform for batch processing as well as real time.
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