What Are The Main Features Of Impala?

1.	What Are The Main Features Of Impala?
Answer» A large set of SQL statements, including SELECT and INSERT, with joins, Subqueries in Impala SELECT Statements, and Impala Analytic Functions. Highly COMPATIBLE with HiveQL, and also including some vendor extensions. For more information. Distributed, high-performance queries. Using Cloudera Manager, you can deploy and manage your Impala SERVICES. Cloudera Manager is the best way to get started with Impala on your cluster. Using Hue for queries. Appending and inserting data into tables through the INSERT statement. ODBC: Impala is certified to run against MicroStrategy and Tableau, with restrictions. For more information, see Configuring Impala to Work with ODBC. Querying data stored in HDFS and HBASE in a single QUERY. In Impala 2.2.0 and higher, querying data stored in the Amazon Simple Storage Service (S3). Concurrent client requests. Each Impala daemon can handle multiple concurrent client requests. The effects on performance depend on your particular hardware and workload. Kerberos authentication. For more information. Partitions. With Impala SQL, you can create partitioned tables with the CREATE TABLE statement, and add and drop partitions with the ALTER TABLE statement. Impala also takes advantage of the partitioning present in Hive tables.

Answer»

A large set of SQL statements, including SELECT and INSERT, with joins, Subqueries in Impala SELECT Statements, and Impala Analytic Functions. Highly COMPATIBLE with HiveQL, and also including some vendor extensions. For more information.
Distributed, high-performance queries.
Using Cloudera Manager, you can deploy and manage your Impala SERVICES. Cloudera Manager is the best way to get started with Impala on your cluster.
Using Hue for queries.
Appending and inserting data into tables through the INSERT statement.
ODBC: Impala is certified to run against MicroStrategy and Tableau, with restrictions. For more information, see Configuring Impala to Work with ODBC.
Querying data stored in HDFS and HBASE in a single QUERY.
In Impala 2.2.0 and higher, querying data stored in the Amazon Simple Storage Service (S3).
Concurrent client requests. Each Impala daemon can handle multiple concurrent client requests. The effects on performance depend on your particular hardware and workload.
Kerberos authentication. For more information.
Partitions. With Impala SQL, you can create partitioned tables with the CREATE TABLE statement, and add and drop partitions with the ALTER TABLE statement. Impala also takes advantage of the partitioning present in Hive tables.

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