{"id":9907,"date":"2018-03-05T09:07:44","date_gmt":"2018-03-05T09:07:44","guid":{"rendered":"https:\/\/data-flair.training\/blogs\/?p=9907"},"modified":"2018-03-05T09:07:44","modified_gmt":"2018-03-05T09:07:44","slug":"hive-features-and-limitations","status":"publish","type":"post","link":"https:\/\/data-flair.training\/blogs\/hive-features-and-limitations\/","title":{"rendered":"Apache Hive Features | Limitations of Hive"},"content":{"rendered":"

As we know to process structured data in Hadoop<\/strong>, we use Hive. Apart from it, there are several features of Apache Hive. well, it also has several limitations.<\/span><\/p>\n

So, in this Hive Tutorial, we will see “Apache Hive features and limitations of Hive”, we will discuss both features and limitations of Hive. But, before that, we will also learn\u00a0the introduction of Hive.<\/span><\/p>\n

What is Apache Hive?<\/span><\/h2>\n

Basically, the tool to process structured data in Hadoop<\/strong> we use Hive. It is a data warehouse infrastructure. Moreover, to summarize Big Data<\/strong>, it resides on top of Hadoop. Also, makes querying and analyzing easy.<\/span><\/p>\n

However, the Apache Software Foundation took it up, but initially, Hive was developed by Facebook. Further Apache Software Foundation developed it as an open-source under the name Apache Hive. Although, many different companies use it. Like, Amazon uses it in Amazon Elastic MapReduce.<\/p>\n

Apache Hive Features and Limitations<\/span><\/h2>\n
\"Apache<\/a>

Apache Hive Features | Limitations of Hive<\/p><\/div>\n

a. Hive Features<\/span><\/h3>\n

Some Hive new features are discussed below:<\/p>\n

i. Framework<\/strong>
\nApache Hive is built on top of Hadoop distributed framework system (HDFS)<\/strong>.<\/span><\/p>\n

ii. Large datasets<\/strong>
\nHowever, in distributed storage, it helps to query large datasets residing.\u00a0<\/span><\/p>\n

iii. Warehouse<\/strong>
\nAlso, we can say Hive is a distributed data warehouse.<\/span><\/p>\n

iv. Language<\/strong>
\nQueries data using a SQL-like language called HiveQL (HQL). <\/span><\/p>\n

v. Declarative language<\/strong>
\nHiveQL is a declarative language like SQL.<\/span><\/p>\n

vi. Table structure<\/strong>
\nTable structure\/s is\/are similar to tables in a relational database. <\/span><\/p>\n

vii. Multi-user<\/strong>
\nMultiple users can simultaneously query the data using Hive-QL. <\/span><\/p>\n

viii. Data Analysis<\/strong>
\nHowever,\u00a0 to perform more detailed data analysis, Hive allows writing custom MapReduce<\/strong> framework processes. <\/span><\/p>\n

ix. ETL support<\/strong>
\nAlso, it is possible to extract\/transform\/load (ETL) Data easily.<\/span><\/p>\n

x. Data Formats<\/strong>
\nMoreover, Hive offers the structure on a variety of data formats. <\/span><\/p>\n

xi. Storage<\/strong>
\nHive allows access files stored in\u00a0HDFS<\/strong>. Also, similar others data storage systems such as Apache HBase<\/strong>.<\/span><\/p>\n

x. Format conversion<\/strong>
\nMoreover, it allows converting the variety of format from to within Hive. Although, it is very simple and possible.<\/span><\/p>\n

b. Limitations of Hive<\/span><\/h3>\n

i. OLTP Processing issues<\/strong>
\nHowever, Hive is not designed for Online transaction processing (OLTP). Although, we can use it for the Online Analytical Processing (OLAP). <\/span><\/p>\n

ii. No Updates<\/strong>
\nIt does not support updates and deletes, however, it does support overwriting or apprehending data. <\/span><\/p>\n

iii. Subqueries<\/strong>
\nBasically, in Hive, Subqueries are not supported.<\/span>\u00a0 \u00a0 \u00a0<\/span>\u00a0 \u00a0<\/span><\/p>\n

So, this was all in Features of Hive. Hope you like our explanation.\u00a0 \u00a0 \u00a0<\/span><\/p>\n

Conclusion<\/span><\/h2>\n

Hence, we have seen all the Hive features and limitations of Hive. Still, if any query occurs feel free to ask in the comment section. \u00a0\u00a0\u00a0\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

As we know to process structured data in Hadoop, we use Hive. Apart from it, there are several features of Apache Hive. well, it also has several limitations. So, in this Hive Tutorial, we...<\/p>\n","protected":false},"author":7,"featured_media":10073,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[26],"tags":[342,1759,3631,4062,4598,5709,5710,5745,8249],"class_list":["post-9907","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-hive","tag-advantages-of-hive","tag-benefits-of-hive","tag-declarative-language","tag-drawbacks-of-hive","tag-features-of-hive","tag-hive-features","tag-hive-features-and-limitations","tag-hive-limitations","tag-limitations-of-hive"],"yoast_head":"\nApache Hive Features | Limitations of Hive - DataFlair<\/title>\n<meta name=\"description\" content=\"Hive tutorial-Hive Features and limitations of Hive-framework,Large datasets,warehouse,language,Declarative language,Multi-user,Data Analysis, ETL support\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/data-flair.training\/blogs\/hive-features-and-limitations\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Apache Hive Features | Limitations of Hive - 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