Category Archives: Tools

Customizing Docker Images in Cloudera Data Science Workbench

Categories: Altus CDH Cloud Data Science How-to Tools

This article shows how to build and publish a customized Docker image for usage as an engine in Cloudera Data Science Workbench. Such an image or engine customization gives you the benefit of being able to work with your favorite tool chain inside the web based application.

Motivation:

Cloudera Data Science Workbench (CDSW) enables data scientists to use their favorite tools such as R, Python, or Scala based libraries out of the box in an isolated secure sandbox environment.

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implyr: R Interface for Apache Impala

Categories: CDH Data Science HBase HDFS Impala Kudu Tools

New R package implyr enables R users to query Impala using dplyr.

Apache Impala (incubating) enables low-latency interactive SQL queries on data stored in HDFS, Amazon S3, Apache Kudu, and Apache HBase. With the availability of the R package implyr on CRAN and GitHub, it’s now possible to query Impala from R using the popular package dplyr.

dplyr provides a grammar of data manipulation,

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Quality Assurance at Cloudera: Highly-Controlled Disk Injection

Categories: CDH Testing Tools

Recently installed fault-injection techniques are making quality assurance processes yet more rigorous.

In a previous installment of our series about quality assurance inside Cloudera, we described the fault-injection frameworks (AgenTEST and Sapper) that Cloudera Engineering has devised. The fault-injection framework starts and stops injections, to determine when and how they should occur, respectively.

On that occasion, we presented a number of disk-related injections implemented in AgenTEST, including:

  • BurnIO: Runs disk-intensive processes,

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Announcing hs2client, A Fast New C++ / Python Thrift Client for Impala and Hive

Categories: Data Science Hive Impala Tools

This new (alpha) C++ client library for Apache Impala (incubating) and Apache Hive provides high-performance data access from Python.

Earlier this year, members of the Python data tools and Impala teams at Cloudera began collaborating to create a new C++ library to eventually become a faster, more memory-efficient replacement for impyla, PyHive, and other (largely pure Python) client libraries for talking to Hive and Impala.

We are excited to release this effort,

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Quality Assurance at Cloudera: Distributed Unit Testing

Categories: Kudu Testing Tools

Cloudera Engineering has developed (and recently open sourced) a distributed unit testing framework that cuts testing time from multiple hours to just 10 minutes.

Upstream unit tests are Cloudera’s first line of defense for finding and fixing software bugs, as part of a multidimensional process that also includes static/dynamic code analysis, fault injection, integration/scale/endurance testing, and validation on real workloads. However, running a full unit test suite for Apache Hadoop ecosystem components can take hours,

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