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<!DOCTYPE concept PUBLIC "-//OASIS//DTD DITA Concept//EN" "concept.dtd">
<concept id="perf_benchmarks">
<title>Benchmarking Impala Queries</title>
<titlealts audience="PDF"><navtitle>Benchmarking</navtitle></titlealts>
<data name="Category" value="Performance"/>
<data name="Category" value="Impala"/>
<data name="Category" value="Querying"/>
<data name="Category" value="Proof of Concept"/>
<data name="Category" value="Developers"/>
<data name="Category" value="Data Analysts"/>
Because Impala, like other Hadoop components, is designed to handle large data volumes in a distributed
environment, conduct any performance tests using realistic data and cluster configurations. Use a multi-node
cluster rather than a single node; run queries against tables containing terabytes of data rather than tens
of gigabytes. The parallel processing techniques used by Impala are most appropriate for workloads that are
beyond the capacity of a single server.
When you run queries returning large numbers of rows, the CPU time to pretty-print the output can be
substantial, giving an inaccurate measurement of the actual query time. Consider using the
<codeph>-B</codeph> option on the <codeph>impala-shell</codeph> command to turn off the pretty-printing, and
optionally the <codeph>-o</codeph> option to store query results in a file rather than printing to the
screen. See <xref href="impala_shell_options.xml#shell_options"/> for details.