What is Apache Hive and Impala?
What is Apache Hive and Impala?
Apache Hive: It is a data warehouse software project built on top of Apache Hadoop for providing data query and analysis. Apache Impala: It is an open-source massively parallel processing SQL query engine for data stored in a computer cluster running Apache Hadoop.
When should I use Impala vs hive?
Using Impala and Hive LLAP
| Impala | Hive LLAP |
|---|---|
| Good choice for interactive and ad-hoc analysis, especially with high concurrency self-service | Good choice for long-running queries requiring heavy transformations or multiple joins Good choice for interactive and ad-hoc analysis using features not available in Impala |
Does Impala need hive?
Hive (optional). Although only the Hive metastore database is required for Impala to function, you might install Hive on some client machines to create and load data into tables that use certain file formats.
Why is Impala faster than Hive?
Your analysts will get their answer way faster using Impala, although unlike Hive, Impala is not fault-tolerance. Impala is faster than Hive because it’s a whole different engine and Hive is over MapReduce (which is very slow due to its too many disk I/O operations).
Why is Hive slower than Impala?
These days, Hive is only for ETLs and batch-processing. Impala is faster than Hive because it’s a whole different engine and Hive is over MapReduce (which is very slow due to its too many disk I/O operations).
Can Impala replace Hive?
Impala does not replace the batch processing frameworks built on MapReduce such as Hive. Hive and other frameworks built on MapReduce are best suited for long running batch jobs, such as those involving batch processing of Extract, Transform, and Load (ETL) type jobs.
Is Impala supported by Apache spark?
Apache Spark supports Hive UDFs (user-defined functions). However, Impala, because of it uses a custom C++ runtime, does not support Hive UDFs.