IMPALA-7550: Add documentation to profile counters

This change changes the way developers define profile counters by
generating counters from a counter registry. All the profile counters
will be register there first and then used in the same way as before.
By doing so, we will be able to manage profile counters in a way that
we can define profile counters documentation. For example:

    "Number of backends running this query.");

COUNTER_SET(PROFILE_NumBackends.Instantiate(query_profile_), num_backends);

This shall be how we define a NumBackends counter. It follows with
its significance, type, description in the declaration part.

Users now will be able to view profile counters documentation under
query_profile page, there is a Profile Documentation button which
leads to /profile_docs.

More details:
This commit did the following refactors on profile counters.
1. Add a singleton registry for runtime profile counters prototypes,
similiar to what Kudu does for metrics. This allows us to generate
profile documentation for all counters from the code. We add
/profile_docs and a correspoding UI for the documentation of profile

2. Profile counters are also annotated with their significance to users.
* STABLE_HIGH - High level and stable counters, always useful for measuring
query performance and status. Counters that everyone is interested. should
rarely change and if it does we will make some effort to notify users.

* STABLE_LOW - Low level and stable counters. Interesting counters to monitor
 and analyze by machine. It will probably be interesting under some
 circumstances for users.

* Unstable - Unstable but useful. Useful to understand query performance,
but subject to change, particularly if the implementation changes.
E.g. MaterializeTupleTimer

* Debug -  Debugging counters. Generally not useful to users of Impala,
 the main use case is low-level debugging. Can be hidden to reduce noise
 for most consumers of profiles.

3. We have around 250 counters. This commit did the replacement in
scan-node and hdfs-scan-node-base and coordinator.

The downside is that we will have duplicate comments of query profiles
both in the header file and the .cc file.
Additionally a (arguably good) limitation is that profile counter names
need to be unique.

Change-Id: Idc03faddb27754001290bb6d899840e2cbe7ccb7
Reviewed-by: Impala Public Jenkins <>
Tested-by: Impala Public Jenkins <>
15 files changed
tree: 66638986f6d341b6cb5e3f3ae7a65eb06ef57082
  1. .clang-format
  2. .clang-tidy
  3. .gitattributes
  4. .gitignore
  5. CMakeLists.txt
  7. LICENSE.txt
  9. NOTICE.txt
  11. be/
  12. bin/
  14. cmake_modules/
  15. common/
  16. docker/
  17. docs/
  18. ext-data-source/
  19. fe/
  20. impala-parent/
  21. infra/
  22. lib/
  23. query-event-hook-api/
  24. security/
  25. setup.cfg
  26. shaded-deps/
  27. shell/
  28. ssh_keys/
  29. testdata/
  30. tests/
  31. www/

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 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.

Supported Platforms

Impala only supports Linux at the moment.

Export Control Notice

This distribution uses cryptographic software and may be subject to export controls. Please refer to for more information.

Build Instructions

See bin/

Detailed Build Notes

Impala can be built with pre-built components or components downloaded from S3. The components needed to build Impala are Apache Hadoop, Hive, HBase, and Sentry. If you need to manually override the locations or versions of these components, you can do so through the environment variables and scripts listed below.

Scripts and directories
bin/impala-config.shThis script must be sourced to setup all environment variables properly to allow other scripts to work
bin/impala-config-local.shA script can be created in this location to set local overrides for any environment variables
bin/impala-config-branch.shA version of the above that can be checked into a branch for convenience.
bin/bootstrap_build.shA helper script to bootstrap some of the build requirements.
bin/bootstrap_development.shA helper script to bootstrap a developer environment. Please read it before using.
be/build/Impala build output goes here.
be/generated-sources/Thrift and other generated source will be found here.
Build Related Variables
Environment variableDefault valueDescription
IMPALA_HOMETop level Impala directory
IMPALA_TOOLCHAIN“${IMPALA_HOME}/toolchain”Native toolchain directory (for compilers, libraries, etc.)
SKIP_TOOLCHAIN_BOOTSTRAP“false”Skips downloading the toolchain any python dependencies if “true”
CDH_BUILD_NUMBERIdentifier to indicate the CDH build number
CDH_COMPONENTS_HOME“${IMPALA_HOME}/toolchain/cdh_components-${CDH_BUILD_NUMBER}”Location of the CDH components within the toolchain.
CDH_MAJOR_VERSION“5”Identifier used to uniqueify paths for potentially incompatible component builds.
IMPALA_CONFIG_SOURCED“1”Set by ${IMPALA_HOME}/bin/ (internal use)
JAVA_HOME“/usr/lib/jvm/${JAVA_VERSION}”Used to locate Java
JAVA_VERSION“java-7-oracle-amd64”Can override to set a local Java version.
JAVA“${JAVA_HOME}/bin/java”Java binary location.
CLASSPATHSee bin/ for details.
PYTHONPATHWill be changed to include: “${IMPALA_HOME}/shell/gen-py” “${IMPALA_HOME}/testdata” “${THRIFT_HOME}/python/lib/python2.7/site-packages” “${HIVE_HOME}/lib/py” “${IMPALA_HOME}/shell/ext-py/prettytable-0.7.1/dist/prettytable-0.7.1” "${IMPALA_HOME}/shell/ext-py/sasl-0.1.1/dist/sasl-0.1.1-py2.7-linux-x "${IMPALA_HOME}/shell/ext-py/sqlparse-0.1.19/dist/sqlparse-0.1.19-py2
Source Directories for Impala
Environment variableDefault valueDescription
IMPALA_BE_DIR“${IMPALA_HOME}/be”Backend directory. Build output is also stored here.
IMPALA_FE_DIR“${IMPALA_HOME}/fe”Frontend directory
IMPALA_COMMON_DIR“${IMPALA_HOME}/common”Common code (thrift, function registry)
Various Compilation Settings
Environment variableDefault valueDescription
IMPALA_BUILD_THREADS“8” or set to number of processors by default.Used for make -j and distcc -j settings.
IMPALA_MAKE_FLAGS""Any extra settings to pass to make. Also used when copying udfs / udas into HDFS.
USE_SYSTEM_GCC“0”If set to any other value, directs cmake to not set GCC_ROOT, CMAKE_C_COMPILER, CMAKE_CXX_COMPILER, as well as setting TOOLCHAIN_LINK_FLAGS
IMPALA_CXX_COMPILER“default”Used by cmake (cmake_modules/toolchain and clang_toolchain.cmake) to select gcc / clang
USE_GOLD_LINKER“true”Directs backend cmake to use gold.
IS_OSX“false”(Experimental) currently only used to disable Kudu.
Environment variableDefault valueDescription
HADOOP_INCLUDE_DIR“${HADOOP_HOME}/include”For ‘hdfs.h’
HADOOP_LIB_DIR“${HADOOP_HOME}/lib”For ‘libhdfs.a’ or ‘’