Advantages and Disadvantages of Apache Spark

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Advantages and Disadvantages of Apache Spark: Apache Spark is one of the Trending project in Apache Foundation From last two years so many hadoop projects are moving from Mapreduce to Apache Spark side because Apache Spark overcome the some main problems in Mapreduce.Now Lets us discuss about Advantages and Disadvantages of Apache Spark .

Advantages and Disadvantages of Apache Spark

Advantages and Disadvantages of Apache Spark

Advantages and Disadvantages of Apache Spark

Advantages of Apache Spark

Apache Spark is a In memory cluster computing platform.

Faster batch processing than MapReduce. Spark executes batch-processing jobs 10 to 100 times faster than MapReduce.

Apache Spark Supports for Sophisticated Analytics.

Apache Spark come up with so many useful ecosystems Like Spark SQL,Spark Graphx,Spark MLlib and Spark Streaming

Spark comes with GraphX, a distributed graph system.

Spark is ideal for iterative processing, interactive processing and event stream processing.

Spark can run on Hadoop alongside other tools in the Hadoop ecosystem including Hive and Pig.

It is very flexible and powerful

Apache Spark Supports Machine Learning Algorithms for Future Predictions

Same platform for real time and Batch Processing

Apache Spark can support Many Languages like Scala,Java,Phython and R.

Apache Spark Can Integrate with HDFS and Hbase and Casendra and other storage systems also .

Disadvantages of Apache Spark

  • It consumes a lot of Memory,and issues around memory consumption are not handled in a user friendly Manner.
  • Apache Spark would take large resources.

This are the main Advantages and Disadvantages of Apache Spark or What are the pros and cons of Apache Spark,benefits of apache spark,What are the limitations of Apache Spark

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