Best 15 Impala Features You Must Know
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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.
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
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.
i. Joins and Functions
Including SELECT, joins, and aggregate functions, Impala offers most common SQL-92 features of Hive Query Language (HiveQL).
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.
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.
It supports Impala-shell command-line interface.
Also, it offers Kerberos authentication.
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.