{"id":576,"date":"2021-07-13T21:50:34","date_gmt":"2021-07-13T21:50:34","guid":{"rendered":"https:\/\/www.wikitechy.com\/interview-questions\/?p=576"},"modified":"2021-09-13T05:32:03","modified_gmt":"2021-09-13T05:32:03","slug":"what-is-a-tool-for-tuning-hive-queries","status":"publish","type":"post","link":"https:\/\/www.wikitechy.com\/interview-questions\/hive\/what-is-a-tool-for-tuning-hive-queries\/","title":{"rendered":"What is a tool for tuning hive queries ?"},"content":{"rendered":"
\n
\n

Tool for tuning hive queries<\/h2>\n<\/div>\n<\/div>\n
\n
\"tool<\/div>\n<\/div>\n
\n
\n

1. Enable Compression in Hive<\/h2>\n<\/div>\n<\/div>\n
\n
\n
    \n
  • By doing compression at various phases (i.e. on final output, intermediate data),we achieve performance improvement in Hive Queries.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n
    <\/div>\n
    \n
    \n

    2. Optimize Joins<\/h2>\n<\/div>\n<\/div>\n

    We can improve the performance of joins.By enabling Auto Convert Map Joins and enabling optimization of skew join.<\/p>\n

    \n
    \n
      \n
    1. Auto Map Join<\/li>\n
    2. Skew Joins<\/li>\n
    3. Enable Bucketed Map Joins<\/li>\n<\/ol>\n<\/div>\n<\/div>\n
      \n
      \n

      Auto Map Join:<\/h2>\n
        \n
      • \n
          \n
        • Auto Map-Join is useful feature when joining a big table with a small table.<\/li>\n
        • If we enable this feature, the small table will be saved in the local cache on each node, joined with the big table in the Map phase.<\/li>\n
        • Enabling Auto Map Join provides 2 advantages.<\/li>\n
        • Primary,it loads a small table into cache will save read time on each data node.<\/li>\n
        • Secondary, it avoids skew joins in the Hive query, since the join operation has been already done in the Map phase for each block of data.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/div>\n<\/div>\n
          \n
          \n

          Skew joins:<\/h2>\n
            \n
          • \n
              \n
            • We enable skew joins by setting hive.optimize.<\/li>\n
            • Skew join property SET command in hive shell or hive-site.xml file.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/div>\n<\/div>\n
              \n
              \n

              Enable Bucketed Map Joins<\/h2>\n
                \n
              • \n
                  \n
                • The tables as specific column and tables used in joins to improve performance bucketed map join is used.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<\/div>\n<\/div>\n
                  \n
                  \n

                  3. Enable Parallel Execution<\/h2>\n<\/div>\n<\/div>\n
                  \n
                  \n
                    \n
                  • Hive converts a query into more stages.The MapReduce stage, sampling stage, a mergestage and a limit stage.<\/li>\n
                  • By default, Hive executes only one time for these satges.<\/li>\n
                  • A particular job may consist of some stages that are not dependent on each other and could be executed in parallel, possibly allowing the overall job to complete more quickly.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n
                    \n
                    \n

                    4. Single Reduce for Multi Group BY<\/h2>\n<\/div>\n<\/div>\n
                    \n
                    \n
                      \n
                    • The single reducer used for multi operations, it combine multiple GROUP BY operations in a query into a single MapReduce job<\/li>\n<\/ul>\n<\/div>\n<\/div>\n
                      \n
                      \n

                      5. Enable Vectorization<\/h2>\n<\/div>\n<\/div>\n
                      \n
                      \n
                        \n
                      • Vectorization introduced into hive for the first time in hive-0.13.1 release only<\/li>\n
                      • It improve operations like scans, aggregations, filters and joins, batches of 1024 rows for each time.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n
                        \n
                        \n

                        6. Enable Cost Based Optimization<\/h2>\n<\/div>\n<\/div>\n
                        \n
                        \n
                          \n
                        • It provided the cost based optimization, based on query cost, resulting in different decisions: how to order joins, which type of join to perform and degree of parallelism.<\/li>\n<\/ul>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

                          Answer : By doing compression at various phases (i.e. on final output, intermediate data),we achieve performance improvement in Hive Queries.<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[3782],"tags":[195,971,3799,203,199,214,209,3878,205,222,484,3881,3876,621,3877,3880,620,3882,196,3716,712,970,366,477,208,288,483,976,975,200,974,197,280,364,3879,968,216,2119,969],"class_list":["post-576","post","type-post","status-publish","format-standard","hentry","category-hive","tag-accenture-interview-questions-and-answers","tag-altimetrik-india-pvt-ltd-interview-questions-and-answers","tag-ani-technologies-pvt-ltd-interview-questions-and-answers","tag-capgemini-interview-questions-and-answers","tag-casting-networks-india-pvt-limited-interview-questions-and-answers","tag-cgi-group-inc-interview-questions-and-answers","tag-collabera-technologies-interview-questions-and-answers","tag-cost-based-query-optimization-in-hive","tag-dell-international-services-india-pvt-ltd-interview-questions-and-answers","tag-flipkart-interview-questions-and-answers","tag-genpact-interview-questions-and-answers","tag-hive-performance-tuning-hortonworks","tag-hive-performance-tuning-techniques","tag-hive-query-based-interview-questions","tag-hive-query-optimization-parameters","tag-hive-query-optimization-techniques","tag-hive-scenario-based-interview-questions","tag-how-will-you-optimize-hive-performance","tag-ibm-interview-questions-and-answers","tag-impetus-technologies-interview-questions-and-answers","tag-indiabulls-technology-solutions-ltd-interview-questions-and-answers","tag-mindtree-interview-questions-and-answers","tag-netapp-interview-questions-and-answers","tag-pig-interview-questions","tag-prokarma-softech-pvt-ltd-interview-questions-and-answers","tag-r-systems-interview-questions-and-answers","tag-reliance-industries-ltd-interview-questions-and-answers","tag-synechron-te-interview-questions-and-answers","tag-tata-consultancy-service-interview-questions-and-answers","tag-tech-mahindra-interview-questions-and-answers","tag-trigent-software-interview-questions-and-answers","tag-unitedhealth-group-interview-questions-and-answers","tag-virtusa-consulting-services-pvt-ltd-interview-questions-and-answers","tag-wells-fargo-interview-questions-and-answers","tag-will-the-reducer-work-or-not-if-you-use-limit-1-in-any-hiveql-query","tag-wipro-infotech-interview-questions-and-answers","tag-wipro-interview-questions-and-answers","tag-yash-technologies-interview-questions-and-answers","tag-yodlee-infotech-pvt-ltd-interview-questions-and-answers"],"yoast_head":"\nWhat 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