This is the first in a series where we’ll highlight some cool queries and share interesting tips and tricks related to ClickHouse. For the first few posts, we will focus on an analysis of the ClickHouse repository using the
git-import tool distributed with ClickHouse.
In this post, we’d like to give some insights back to our community. The Github archive dataset has been the foundation for examples and demos for some time. While a great resource, it doesn’t track the details of repositories at a code level, e.g., commits and changes to lines of code, but instead focuses on issues, stars, PRs, and events. Meanwhile, Git insights (via pulse) are interesting but incomplete…and exploring ClickHouse is substantially more fun.
Fortunately, a tool is distributed with ClickHouse that solves this very issue: the
ClickHouse % clickhouse-git-import -h A tool to extract information from Git repository for analytics. It dumps the data for the following tables: - commits - commits with statistics; - file_changes - files changed in every commit with the info about the change and statistics; - line_changes - every changed line in every changed file in every commit with full info about the line and the information about previous change of this line. The largest and the most important table is "line_changes". Run this tool inside your git repository. It will create .tsv files that can be loaded into ClickHouse (or into other DBMS if you dare).
For the ClickHouse repository, this generates files of the following sizes in a few minutes as of November 8th, 2022:
commits.tsv- 7.8M - 266,051 rows
file_changes.tsv- 53M - 266,051 rows
line_changes.tsv- 2.7G - 7,535,157 rows
You can generate this data for any repository on Github (see linux here) and analyze your own projects using the questions below for inspiration. If you don’t have time to generate the data yourself, we’ve loaded our own data into play.clickhouse.com (note the database is
git_clickhouse) so our community can play with the example queries.
The tool handily proposes some possible questions for you to answer. We’ve answered these, in addition to some others of interest, for the ClickHouse repository. You can find the complete list of questions and their current answers here. Please share your own insights for both ClickHouse and other repositories, and feel free to contribute queries and improvements!
Note that some of the questions are quite broad and open to interpretation, so we welcome alternatives. The data is also intended for high-level analytical purposes. It can be imprecise for a few reasons (e.g., dirty and broken commit histories), making some more exact queries particularly challenging. This shouldn’t impact any high-level analysis, however.
In future posts, we’ll dig into some specific queries and highlight a range of ClickHouse functionality. For now, we’d like to present the opportunity to solve one of the tools suggested questions for which the current answer feels like it could be improved….
The most challenging query posed by the tool is probably the reconstruction of the git blame command. As a reminder,
git blame shows the current file, annotating each line in the given file with information from the revision that last modified the line. For example,
ClickHouse % git blame src/Storages/StorageReplicatedMergeTree.cpp | head Blaming lines: 100% (8630/8630), done. cdeda4ab915 src/Storages/StorageReplicatedMergeTree.cpp (Alexey Milovidov 2020-04-15 23:28:05 +0300 1) #include cdeda4ab915 src/Storages/StorageReplicatedMergeTree.cpp (Alexey Milovidov 2020-04-15 23:28:05 +0300 2) b40d9200d20 src/Storages/StorageReplicatedMergeTree.cpp (Anton Popov 2022-10-23 03:29:26 +0000 3) #include 210882b9c4d src/Storages/StorageReplicatedMergeTree.cpp (alesapin 2022-10-03 23:30:50 +0200 4) #include 4c391f8e994 src/Storages/StorageReplicatedMergeTree.cpp (Mike Kot 2021-06-20 11:24:43 +0300 5) #include "Common/hex.h" a6ca9f266f1 dbms/src/Storages/StorageReplicatedMergeTree.cpp (Alexey Milovidov 2019-05-03 05:00:57 +0300 6) #include a6ca9f266f1 dbms/src/Storages/StorageReplicatedMergeTree.cpp (Alexey Milovidov 2019-05-03 05:00:57 +0300 7) #include 3e5ef56644b dbms/src/Storages/StorageReplicatedMergeTree.cpp (Alexander Burmak 2019-11-27 12:39:44 +0300 8) #include 3e5ef56644b dbms/src/Storages/StorageReplicatedMergeTree.cpp (Alexander Burmak 2019-11-27 12:39:44 +0300 9) #include 3e5ef56644b dbms/src/Storages/StorageReplicatedMergeTree.cpp (Alexander Burmak 2019-11-27 12:39:44 +0300 10) #include
Reconstructing this from a history of commits is particularly challenging - especially since ClickHouse doesn’t currently have an
arrayReduce function which iterates with the current state. Our documentation has an approximate solution appropriate for high-level analysis, but we hope you can improve this.
We leave this to the reader to solve - with a t-shirt for the first to present their answer - tweet us at @ClickHouse, send us an email at [email protected] with the title “git blame solution” or just raise a PR on the doc page.
A few tips:
- When comparing your query result with
git-blame, make sure you check out the same commit for which this dataset was generated up to - if using play, check the latest commit here. This is the same as the distributed datasets available here.
- Also, consider that files can be renamed, and thus changes can be logged under different paths. We have solved this for you with a UDF, which gives you the complete change history. See here.
line_changestable has a row for every line change - see the
linefield, as well as the time and commit. The
signfield indicates if the lines were an insertion (1) or deletion (-1).
- The insertion and deletion of a line cause the position of all previous lines, at that moment in line, to change by 1 or -1, respectively.
A completely accurate answer is unlikely for all files due to issues in the commit history. An answer which is close, with justifications for discrepancies attributed to the data, will therefore be accepted. If an exact solution is not submitted by December 14th, the closest and current accepted solution will win.
For those of you wanting to participate, ClickHouse Cloud is a great starting point to solve the challenge - spin up a cluster, load the data, let us deal with the infrastructure, and get querying!
In this post, we’ve introduced the
git-import tool and presented a query for our community to solve, with a t-shirt prize at stake! We encourage readers to explore the full list of questions and current answers and hope our community finds value in this data. In future posts, we’ll dive into some of the specific queries.