Tag Archives: analytics

How-to: Use HUE’s Notebook App with SQL and Apache Spark for Analytics

Categories: How-to Hue Spark

This post from the HUE team about using HUE (the open source web GUI for Apache Hadoop), Apache Spark, and SQL for analytics was initially published in the HUE project’s blog.

Apache Spark is getting popular and HUE contributors are working on making it accessible to even more users. Specifically, by creating a Web interface that allows anyone with a browser to type some Spark code and execute it.

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How-to: Use Apache Solr to Query Indexed Data for Analytics

Categories: How-to Search

Bet you didn’t know this: In some cases, Solr offers lightning-fast response times for business-style queries.

If you were to ask well informed technical people about use cases for Solr, the most likely response would be that Solr (in combination with Apache Lucene) is an open source text search engine: one can use Solr to index documents, and after indexing, these same documents can be easily searched using free-form queries in much the same way as you would query Google.

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How-to: Build a Machine-Learning App Using Sparkling Water and Apache Spark

Categories: CDH Data Science Guest How-to Spark

Thanks to Michal Malohlava, Amy Wang, and Avni Wadhwa of H20.ai for providing the following guest post about building ML apps using Sparkling Water and Apache Spark on CDH.

The Sparkling Water project is nearing its one-year anniversary, which means Michal Malohlava, our main contributor, has been very busy for the better part of this past year. The Sparkling Water project combines H2O machine-learning algorithms with the execution power of Apache Spark.

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Continuous Distribution Goodness-of-Fit in MLlib: Kolmogorov-Smirnov Testing in Apache Spark

Categories: Spark

Thanks to former Cloudera intern Jose Cambronero for the post below about his summer project, which involved contributions to MLlib in Apache Spark.

Data can come in many shapes and forms, and can be described in many ways. Statistics like the mean and standard deviation of a sample provide descriptions of some of its important qualities. Less commonly used statistics such as skewness and kurtosis provide additional perspective into the data’s profile.

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Kudu: New Apache Hadoop Storage for Fast Analytics on Fast Data

Categories: Hadoop HBase HDFS Impala Kudu Performance Spark

This new open source complement to HDFS and Apache HBase is designed to fill gaps in Hadoop’s storage layer that have given rise to stitched-together, hybrid architectures.

The set of data storage and processing technologies that define the Apache Hadoop ecosystem are expansive and ever-improving, covering a very diverse set of customer use cases used in mission-critical enterprise applications. At Cloudera, we’re constantly pushing the boundaries of what’s possible with Hadoop—making it faster,

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