Category Archives: Hadoop Hive

Hadoop, Hadoop Hive, YARN

Live Long and Process

One great thing about working for Hortonworks is that you get to try out new features before they are released, with real feature engineers as tour guides—features like LLAP, which stands for Live Long and Process. LLAP is coming to Hortonworks with Hive 2.0 and (spoiler alert) it looks like it will be worth the wait.Live-Long-and-Prosper-Shirt

Originally a pure batch processing platform, Hive has speeded up enormously over the last couple of years with Tez, the cost-based optimizer (CBA), ORC files, and a host of other improvements. Queries that once took minutes now (1st quarter 2016) run at interactive speeds, and LLAP aims to push latencies into the sub-second range.

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Hadoop, Hadoop Hive

Lipwig for Hive Is The Greatest!

Making_Money_LipwigOk, this is the coolest thing this Hive user has seen all day.

As you probably know, if you prepend the word EXPLAIN to your SQL query and then run it, Hive prints out a text description of the query plan. This lets you explore the effects such variations as code changes, the use of analyze, turning on/off the cost-based optimizer (CBO), and so on. It’s an essential tool for optimizing Hive.

The output of EXPLAIN is far from pretty, but fortunately, a simple pipeline of Linux commands can give you a slick graphical rendition like the one below.

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Hadoop Hive

Shifting to Hive Part II: Best Practices and Optimizations

This is part two of an extended article. See part one here.

beehive

A full listing of Hive best practices and optimization would fill a book. All we’ll do here is skim over the topics that best indicate the spirit of Hive, and how it is used most successfully. There’s plenty of detail available in the documentation and on the Web at large.  Hopefully, these quick run-downs will provide enough background and keywords for a rewarding Google search.

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Hadoop Hive

Shifting to Hive Part I: Origins

SQL is the lingua-franca of data big and small, but SQL is a language, not a platform—it serves as the conceptual framework for data tasks on many platforms, ranging from blog content management with MySQL, to high-frequency online transaction processing (OLTP) systems, to heavy-duty batch processing on Hadoop and other big-data platforms.

BeehiveWoodcut

I hope this page will help people who are experienced with conventional RDBMS’s and OLTP systems make the jump to working with big data using Apache Hive, the most important of the SQL big-data platforms.

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