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Apache Hive uses a Hive Query language, which is a declarative language similar to SQL. This chapter explains how to use the SELECT statement with WHERE clause. One of the most important pieces of Spark SQL’s Hive support is interaction with Hive metastore, which enables Spark SQL to access metadata of Hive tables. Starting from Spark 1.4.0, a single binary build of Spark SQL can be used to query different versions of Hive metastores, using the … WARN Query: Query for candidates of org.apache.hadoop.hive.metastore.model.MDatabase and subclasses resulted in no possible candidates Required table missing: "DBS" in Catalog "" Schema "". The Working Query. So in the example you provided you will have to change the query to look something like below: SELECT * FROM "TBLS"; HTH As a workaround, set up an external Hive metastore that uses version 2.3.0 or above. Use MYSQL as Meta storage at backend to connect multiple users with Hive at a time SELECT statement is used to retrieve the data from a table. Hive provides SQL type querying language for the ETL purpose on top of Hadoop file system.. Hive Query language (HiveQL) provides SQL type environment in Hive to work with tables, databases, queries. The Thrift interfaces include Drivers, which are processes that interpret the query. By default, Apache Hive uses a built-in Derby SQL server for this purpose. The Hive Query Language (HiveQL) is a query language for Hive to process and analyze structured data in a Metastore. You can implement the Hive Metastore using the tables in a relational database such as MySQL. Hive-Metastore. Why to Use MySQL in Hive as Metastore: By Default, Hive comes with derby database as metastore. The maximum number of registered catalogs that you can have is 1,000. Derby is the default database for the Hive metastore. It is implemented using tables in a relational database. Derby database can support only single active user at a time ; Derby is not recommended in production environment ; So the solution here is . It supports developers to perform processing and analyses on structured and semi-structured data by replacing complex java MapReduce programs with hive queries. DataNucleus requires this table to perform its persistence operations. This is a bug that was fixed in Hive Metastore version 2.3.0 . Azure Databricks uses an earlier version of Hive Metastore (version 0.13), so this bug occurs when there is too much metadata for a column, such as an imported JSON schema. You can use CTAS to create an AWS Glue table from a query on an external Hive metastore, but not to create a table on an external Hive metastore.. You can use INSERT INTO to insert data into an AWS Glue table from a query on an external Hive metastore, but not to insert data into an external Hive metastore. @Vishal Prakash Shah The Hive Metastore database in PgSQL uses upper case object names. The hive metastore DB is a normal MySQL/etc database with a hive schema in it. The hive schema holds the hive tables though. In PostgreSQL to access these upper case objects you have to quote those objects. We can have a different type of Clauses associated with Hive to perform different type data manipulations and querying. All Hive implementations need a metastore service, where it stores metadata. By default, Hive uses a built-in Derby SQL server. Solution. All the metadata for Hive tables and partitions are accessed through the Hive Metastore. So, the information schema is irrelevant to hive; to get the hive table details, you have to interrogate the TBLS table, for example. Hive translates the hive queries into MapReduce programs. 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