HP injects more Hadoop into Vertica with Dragline
The race to deliver the industry’s first end-to-end Big Data platform continues apace. Hewlett-Packard this week pulled the curtains back on a new version of its Vertica analytic database that makes processing large volumes of highly varied information more feasible for economic-minded organizations with existing technology investments to sustain.
Dragline, as the new release is called, comes with a homegrown feature called HP Dynamic Workload Management that optimizes the amount of resources used based on the requirements of individual queries. That means a decision maker looking to answer a specific question about their business or customers should receive results much faster than a data scientist scanning thousands of metrics at once.
To make it even more practical for ordinary users to uncover insights, Dragline introduces enhanced structured query capabilities for Hadoop that HP says provides increased flexibility when using SQL syntax sifting through vast troves of historical data, which can now be stored directly in HDFS. That allows organizations to take advantage of the economies that have set the platform apart and entirely avoid the overhead associated with moving petabytes of information around before every action.
The improvements check both boxes in the company’s development roadmap for the batch processing framework, abstracting away more of the details that have historically made large-scale clusters unwieldy while streamlining the analysis process itself.
“When we look at Hadoop, we have two perspectives and two areas that we want to address,” remarked HP chief Hadoop technologist Steve Watt in an interview on SiliconANGLE’s theCUBE, which will be returning to San Jose next week to stream live news and analysis from Hadoop Summit 2014. “One, there is a lot of platform complexity, so customers struggle to understand what hardware to buy, how to configure that hardware and how to manage that hardware. And then the other aspect is application complexity: how to apply Hadoop to solve business problems. HP as a whole is focusing on those areas.”
Dragline extends that strategic focus with the addition of support for the Hadoop-specific Parquet and Avro data formats as well as the CEF open log management standard and the Apache Thrift framework, which was originally created by Facebook to simplify the development of cross-platform services.
In addition, the release brings with it a text search feature that enables users to look for specific keywords across not only documents and web pages but also machine-generated logs and output generated by the new sentiment analysis engine included in the platform. The company says that the tool, which was designed with short snippets of freeform text like tweets in mind, makes it possible to correlate data about consumer needs with location and business information in a single environment without having to shuffle information in and out of disparate tools.
image via HP
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