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3 Benefits of Apache Hive View 2.0

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3 Benefits of Apache Hive View 2.0

Apache Hive 2.0 has a great UX and various extra functionalities to help you make SQL queries run faster. Get details of the new additions in Ambari's Hive View.

· Big Data Zone ·
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Hortonworks Sandbox for HDP and HDF is your chance to get started on learning, developing, testing and trying out new features. Each download comes preconfigured with interactive tutorials, sample data and developments from the Apache community.

Ambari’s Hive View gives analysts and DBAs a convenient web interface to Apache Hive which allows SQL analytics, data management, and performance diagnostics. Ambari 2.5 introduces Hive View 2.0 with a brand new user experience plus a slew of great new tools to help DBAs run Hive jobs faster and more effectively than ever before.

1. Database Manager Means Hadoop Is Not a Black Box

Ever feel like Hadoop is a black box? Struggling to find what data is in your Hadoop cluster, or how it is laid out?

Hive View 2.0’s new Database Manager makes it easy to:

  • See all Hive databases, including the tables and column definition within.
  • Create your own tables, including ACID tables, partitioning and bucketing.
  • View and export the DDL of any table.

2. Keep Queries Running Fast With Column Statistics

Missing column statistics is one of the leading causes of sub-optimal query performance on Hadoop. Hive View 2.0 makes it easy to view table statistics and find tables that are missing statistics. If you find a table that is missing statistics, computing stats is just one button click away.

  • View statistics for any table or column.
  • Compute table and column stats with one click.

3. Check Under the Hood With the Visual Explain Plan

Slow query got you down? Hive View 2.0’s new Visual Explain makes it easy to find and fix expensive operations by providing a high-level view of the query’s execution plan that focuses on the cost of each step. Expensive operations like Merge Joins are immediately visible, letting you know when settings changes or query re-writes are appropriate. When you need more detail, drill down to any step of the plan to see detailed cost, vectorization, and execution engine information.

  • See the most expensive parts of the query plan with a simple visualization.
  • Quickly spot expensive operations like Merge Joins or Cross Products.

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Topics:
big data ,data analytics ,apache hive ,ambari ,hive view 2.0

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