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Spark History Server and monitoring jobs performance

Imagine a situation that you wrote a spark job for processing huge amount of data and it took 2 days for this job to finish. It happens. Actually, it happens regularly. To tune these jobs engineers need information. It can be obtained from spark events(if you run something on a cluster in Spark...

Spark tips. DataFrame API

There are many different tools in the world, each of which solves a range of problems. Many of them are judged by how well and correct they solve this or that problem, but there are tools that you just like, you want to use them. They are properly designed and fit well in your hand, you do not...

Big Data file formats

Apache Spark supports many different data formats, such as the ubiquitous CSV format and web-friendly JSON format. Common formats used primarily for big data analytical purposes are Apache Parquet and Apache Avro. In this post, we’re going to cover the properties of these 4 formats — CSV, JSON,...

Spark. Anatomy of Spark application

Apache Spark is considered as a powerful complement to Hadoop, big data’s original technology. Spark is a more accessible, powerful and capable big data tool for tackling various big data challenges. It has become mainstream and the most in-demand big data framework across all major industries....

Spark core concepts explained

Apache Spark is considered as a powerful complement to Hadoop, big data’s original technology. Spark is a more accessible, powerful and capable big data tool for tackling various big data challenges. It has become mainstream and the most in-demand big data framework across all major industries....

Things you need to know about Hadoop and YARN being a Spark developer

Apache Spark is considered as a powerful complement to Hadoop, big data’s original technology. Spark is a more accessible, powerful and capable big data tool for tackling various big data challenges. It has become mainstream and the most in-demand big data framework across all major industries....