Best 15 Impala Features You Must Know

1. Impala Features – Objective

As we know to overcome the slowness of Hive Queries, Cloudera offers a separate tool what we call Impala. However, there are many more features of Impala, which makes it best. So, in this article, “Impala features”, we will discuss all Impala features in detail. But before that, we will also learn brief Introduction to Impala to understand it well. 

Impala Features

Best 15 Impala Features You Must Know

2. What is Impala?

Basically, an open source project which is opening up the Apache Hadoop software stack to a wide audience of database analysts, users, and developers. Also, we can perform interactive, ad-hoc and batch queries together in the Hadoop system, by using Impala’s MPP (M-P-P) style execution along with other Hadoop processing MapReduce frameworks.
Basically, for SQL queries distributed across clusters of connected machines the Impala software is written from the ground up for high performance.
Follow this link to know more about What is Impala 

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3. Best Impala Features

There are several features of Impala, let’s discuss all the Impala features one by one−

a. Open Source

Basically, under the Apache license, Impala is available freely as open source.

b. In-memory Processing

While it’s come to processing, Cloudera Impala supports in-memory data processing. That implies without any data movement it accesses/analyzes data that is stored on Hadoop data nodes.

c. Easy Data Access

However, using SQL-like queries, we can easily access data using Impala. Moreover, Impala offers Common data access interfaces. That includes:
i. JDBC driver.
ii. ODBC driver.

d. Faster Access

While we compare Impala to another SQL engines, Impala offers faster access to the data in HDFS.

e. Storage Systems

We can easily store data in storage systems such as HDFS, Apache HBase, and Amazon s3.
i. HDFS file formats: Delimited text files, Parquet, Avro, SequenceFile, and RCFile.
ii. Compression codecs: Snappy, GZIP, Deflate, BZIP.

f. Easy Integration

It is possible to integrate Impala with business intelligence tools such as Tableau, Pentaho, Micro strategy, and Zoom data.

g. File Formats

There are several file formats which Impala supports like LZO, Sequence File, Avro, RCFile, and Parquet.

h. Drivers from Hive

There is one advantage, Impala uses from Hive. That is its metadata, ODBC driver, and SQL syntax.

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i. Joins and Functions

Including SELECT, joins, and aggregate functions, Impala offers most common SQL-92 features of Hive Query Language (HiveQL).

j. Developed

Basically, Cloudera Impala is written in C++ and Java languages.

k. Relational model

One of the major points is Impala follows the Relational model.

l. Data Model

However, Impala’s data model is Schema-based in nature.

m. API’s

While it comes to API’s, Impala offers JDBC and ODBC API’s.

n. Languages Support

Moreover, it supports all languages supporting JDBC/ODBC.

o. High Performance

While we compare Impala to another SQL engines, Impala offers high performance and low latency for Hadoop.

p. Query UI

Moreover, it supports, Hue Beeswax and the Cloudera Impala Query UI.

q. CLI

It supports Impala-shell command-line interface.

r. Authentication

Also, it offers Kerberos authentication.

4. Conclusion

As a result, we have seen all the Impala features which make it best. Still, if any query occurs regarding, feel free to ask in the comment section.
Reference

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