pg_hint_plan VS ClickHouse

Okay so it isn't entirely clear to me, can the pg_hint_plan extension (linked in the OP) do the simple thing where we specify, for each table, which index to use?

I can't find it here

https://github.com/ossc-db/pg_hint_plan/blob/master/docs/hin...

Because, the mssql WITH(INDEX()) is simple and intuitive. This hint table stuff seems complicated, and it's unclear to me if they can do the simple thing

pg_hint_plan —— Give PostgreSQL ability to manually force some decisions in execution plans. https://github.com/ossc-db/pg_hint_plan

I really wish the PostgreSQL core team would acknowledge that their stance on that hurts more than helps. Even Oracle with decades of engineering behind it doesn't get execution plans correct 100% of the time and provides a way to tune query execution via hints.

However, TIL that https://github.com/ossc-db/pg_hint_plan exists so that will probably become a standard thing I deploy.

With PostgreSQL, the extension to do it, pg_hint_plan is really good, but not widely used because not included in the core, not even in contrib. The consequence is that people install it only when needing it, without the time to learn hot to hint properly, may think that "my hint is not used" and give up.

cat > Dockerfile <<'DOCKERFILE' # install pg_hint_plan from rpm FROM docker.io/postgres:14 ADD https://github.com/ossc-db/pg_hint_plan/releases/download/REL14_1_4_0/pg_hint_plan14-1.4-1.el8.x86_64.rpm . RUN apt-get update -y ; apt-get install -y alien wget ; alien ./pg_hint_plan*.rpm ; dpkg -i pg-hint-plan*.deb # copy the minimal files to a postgres image FROM docker.io/postgres:14 COPY --from=0 /usr/pgsql-14/share/extension/pg_hint_plan.control /usr/share/postgresql/14/extension COPY --from=0 /usr/pgsql-14/share/extension/pg_hint_plan--1.4.sql /usr/share/postgresql/14/extension COPY --from=0 /usr/pgsql-14/lib/pg_hint_plan.so /usr/pgsql-14/lib/pg_hint_plan.so /usr/lib/postgresql/14/lib ENV PGPASSWORD=postgres CMD ["postgres","-c","shared_preload_libraries=pg_hint_plan,pg_stat_statements"] DOCKERFILE docker build -t pachot/pg_hint_plan --platform=linux/amd64 . docker push pachot/pg_hint_plan

there is a maintained index hint extension: https://github.com/ossc-db/pg_hint_plan - at least as far as 13 (and likely 14).

if we're going to talk about index functionality that would be good and effective for Postgres, an index across all partitioned tables (both normal and unique) would be very much welcomed.

the problem is finding someone to maintain it for life.

Yes, we are working on it! :) Taking some of the learnings from current experimental JSON Object datatype, we are now working on what will become the production-ready implementation. Details here: https://github.com/ClickHouse/ClickHouse/issues/54864

Variant datatype is already available as experimental in 24.1, Dynamic datatype is WIP (PR almost ready), and JSON datatype is next up. Check out the latest comment on that issue with how the Dynamic datatype will work: https://github.com/ClickHouse/ClickHouse/issues/54864#issuec...

In our repository, I've set up a few hard limits: each translation unit cannot spend more than a certain amount of memory for compilation and a certain amount of CPU time, and the compiled binary has to be not larger than a certain size.

When these limits are reached, the CI stops working, and we have to remove the bloat: https://github.com/ClickHouse/ClickHouse/issues/61121

Although these limits are too generous as of today: for example, the maximum CPU time to compile a translation unit is set to 1000 seconds, and the memory limit is 5 GB, which is ridiculously high.

I have a project dedicated to this topic: https://github.com/ClickHouse/ClickBench

It is important to explain the limitations of a benchmark, provide a methodology, and make it reproducible. It also has to be simple enough, otherwise it will not be realistic to include a large number of participants.

I'm also collecting all database benchmarks I could find: https://github.com/ClickHouse/ClickHouse/issues/22398

ClickHouse: A fast open-source column-oriented database management system. ClickHouse is designed for real-time analytics on large datasets and excels in high-speed data insertion and querying, making it ideal for real-time monitoring and reporting.

Today we're going to create an UDF (User-defined Function) in Golang that can be run inside Clickhouse query, this function will parse uuid v1 and return timestamp of it since Clickhouse doesn't have this function for now. Inspired from the python version with TabSeparated delimiter (since it's easiest to parse), UDF in Clickhouse will read line by line (each row is each line, and each text separated with tab is each column/cell value):

For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules.

Online analytical processing (OLAP) databases like Apache Druid, Apache Pinot, and ClickHouse shine in addressing user-initiated analytical queries. You might write a query to analyze historical data to find the most-clicked products over the past month efficiently using OLAP databases. When contrasting with streaming databases, they may not be optimized for incremental computation, leading to challenges in maintaining the freshness of results. The query in the streaming database focuses on recent data, making it suitable for continuous monitoring. Using streaming databases, you can run queries like finding the top 10 sold products where the “top 10 product list” might change in real-time.

Proton is a lightweight streaming processing "add-on" for ClickHouse, and we are making these delta parts as standalone as possible. Meanwhile contributing back to the ClickHouse community can also help a lot.

Please check this PR from the proton team: https://github.com/ClickHouse/ClickHouse/pull/54870

curl https://clickhouse.com/ | sh

But I continue to find garbage in some of our CI scripts.

Here is an example: https://github.com/ClickHouse/ClickHouse/pull/58794/files

The right way is to:

- always pin versions of all packages;