98d7b8a90d
Before this patch, we would first convert the Decimal to Double, then Double to Timestamp. This resulted in imprecise results. I ran a benchmark where we read decimal values from a large parquet table and cast them to timestamp. The new correct implementation is slightly slower than the old one (101 seconds vs 70 seconds). Change-Id: Iabeea9f4ab4880b2f814408add63c77916e2dba9 Reviewed-on: http://gerrit.cloudera.org:8080/3154 Reviewed-by: Dan Hecht <dhecht@cloudera.com> Tested-by: Internal Jenkins
Welcome to Impala
Lightning-fast, distributed SQL queries for petabytes of data stored in Apache Hadoop clusters.
Impala is a modern, massively-distributed, massively-parallel, C++ query engine that lets you analyze, transform and combine data from a variety of data sources:
- Best of breed performance and scalability.
- Support for data stored in HDFS, Apache HBase and Amazon S3.
- Wide analytic SQL support, including window functions and subqueries.
- On-the-fly code generation using LLVM to generate CPU-efficient code tailored specifically to each individual query.
- Support for the most commonly-used Hadoop file formats, including the Apache Parquet (incubating) project.
- Apache-licensed, 100% open source.
More about Impala
To learn more about Impala as a business user, or to try Impala live or in a VM, please visit the Impala homepage.
If you are interested in contributing to Impala as a developer, or learning more about Impala's internals and architecture, visit the Impala wiki.
Building Impala
This Apache Incubator repository is currently not buildable but has the complete source code for Impala minus some third-party dependences. See https://github.com/cloudera/Impala for the buildable Impala source and https://issues.cloudera.org/browse/IMPALA-3223 to track progress on making this repository buildable.