Github user sraghunandan commented on a diff in the pull request:
https://github.com/apache/carbondata/pull/2568#discussion_r207430412
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+# Performance Report Of Presto combined with Carbondata
+Presto is a MPP (Massively Parallel Processing) tool designed to
efficiently query vast amounts of data using distributed queries. Presto can be
and has been extended to operate over different kinds of data sources including
traditional relational databases and other data sources such as Cassandra. It
is capable of handling data warehousing and analytics: data analysis,
aggregating large amounts of data and producing reports. These workloads are
often classified as Online Analytical Processing (OLAP).
+
+On the other side, Apache Spark is a lightning-fast cluster computing
technology, designed for fast computation. It is based on Hadoop MapReduce and
it extends the MapReduce model to efficiently use it for more types of
computations, which includes interactive queries and stream processing. The
main feature of Spark is its in-memory cluster computing that increases the
processing speed of an application.
+
+While dealing with Carbondata, both of them have their own advantage but
presto is far better than spark while executing 90% of the queries. As the
Presto-carbon vector readers are much optimized and reduces the table scan time
dealing with large table. Even in case of dictionary aggregation and multiple
table join, presto performs much better due to its own optimised way of dealing
with properties.
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remove the work far better.
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