Category Archives: Guest

Scan Improvements in Apache HBase 1.1.0

Categories: Guest HBase

The following post, from Cloudera intern Jonathan Lawlor, originally appeared in the Apache Software Foundation’s blog.

Over the past few months there have a been a variety of nice changes made to scanners in Apache HBase. This post focuses on two such changes, namely RPC chunking (HBASE-11544) and scanner heartbeat messages (HBASE-13090). Both of these changes address long standing issues in the client-server scan protocol.

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Working with Apache Spark: Or, How I Learned to Stop Worrying and Love the Shuffle

Categories: Guest Spark

Our thanks to Ilya Ganelin, Senior Data Engineer at Capital One Labs, for the guest post below about his hard-earned lessons from using Spark.

I started using Apache Spark in late 2014, learning it at the same time as I learned Scala, so I had to wrap my head around the various complexities of a new language as well as a new computational framework. This process was a great in-depth introduction to the world of Big Data (I previously worked as an electrical engineer for Boeing),

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Text Mining with Impala

Categories: Guest Impala Use Case

Thanks to Torsten Kilias and Alexander Löser of the Beuth University of Applied Sciences in Berlin for the following guest post about their INDREX project and its integration with Impala for integrated management of textual and relational data.

Textual data is a core source of information in the enterprise. Example demands arise from sales departments (monitor and identify leads), human resources (identify professionals with capabilities in ‘xyz’), market research (campaign monitoring from the social web),

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Using Apache Parquet at AppNexus

Categories: Guest Impala Parquet Performance

Thanks to Chen Song, Data Team Lead at AppNexus, for allowing us to republish the following post about his company’s use case for Apache Parquet (incubating at this writing), the open standard for columnar storage across the Apache Hadoop ecosystem.

At AppNexus, over 2MM log events are ingested into our data pipeline every second. Log records are sent from upstream systems in the form of Protobuf messages. Raw logs are compressed in Snappy when stored on HDFS.

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How Used Spark Streaming to Build a Near Real-Time Dashboard

Categories: Cloudera Labs Flume Guest Spark Use Case

Thanks to Sam Shuster, Software Engineer at, for the guest post below about his company’s use case for Spark Streaming, SparkOnHBase, and Morphlines.

Every year, the Super Bowl brings parties, food and hopefully a great game to appease everyone’s football appetites until the fall. With any event that brings in around 114 million viewers with larger numbers each year, Americans have also grown accustomed to commercials with production budgets on par with television shows and with entertainment value that tries to rival even the game itself.

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