Apache Hadoop and apache spark hot trend in IT. Many Bigdata institutes offering hadoop and spark training in Hyderabad, but why hadoop and spark i am explaining here.

spark Vs hadoop

Past decades, RDBMS only king to analyze data, Similarly in Programming Java is king to process data. These traditional technologies intentionally implemented for small amount of data with many limitations. So that Second generation technologies like Hadoop came into picture to process large amount of data, but its very slow. Hadoop solve storage problems, analyze offline (batch) data. But in now days different types of data like online (live), offline (batch), machine learning, graphical data coming.  Hadoop not suitable to process this type data, thats why Spark came into picture.

Apache Spark is third generation (current) platform to resolve all bigdata problems.  Spark can resolve all bigdata problems, let example.
Share market share market always fluctuating , if you want to analyze what happend for the last 5 years (5TB ) data and today (1gb live) data, hadoop takes a lot of time, its difficult to process today data. Similarly banking industry. Now you withdraw 10,000 in Mumbai within 5 hour you withdraw 20,000 from chennai. Usually, it’s not possible, so instantly analyze (live) data and stop/block such transaction. To do this type  analyze apache spark, the best suitable framework to process batch data, live data process at a time. Now a days most of the organizations generating this type of data only. So that most of the companies looking for spark developers. So that most of the Spark institutes in mumbai and many online  spark training centers offering with good offers.

The power of spark is architecture.  Spark everything processed in memory so that it’s third generation technology. In future also all frameworks following same architecture (in-memory). Spark 100 times faster than Hadoop processing engine (mapreduce). So spark is origin for future trending technologies like apache flink (it’s for IOT), beam and apache ignite.

Hadoop Vs Spark

Both Hadoop and Spark using 1.x and 2.x means Hadoop 2.x version improve the performance. Similarly Spark 2.0 next releases improves performance. Both Hadoop and Spark run on the top of HDFS & YARN only. So to take any bigdata training everyone must aware of HDFS & YARN. Please note Hadoop not replacement of hadoop & Spark is not replacement of Hadoop. Spark just replacement of Mapreduce (Hadoop processing engine). Both frameworks for OLAP operations only, but not for OLTP operations. To take Spark online training sql experience and core java knowledge highly recommended, but not mandatory.

Why Hadoop? Why Spark?

Leave a Reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.