yugabyte-db
pev2
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yugabyte-db | pev2 | |
---|---|---|
87 | 40 | |
8,486 | 2,363 | |
1.3% | 3.4% | |
10.0 | 7.7 | |
2 days ago | 10 days ago | |
C | TypeScript | |
GNU General Public License v3.0 or later | PostgreSQL License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
yugabyte-db
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Best Practice: use the same datatypes for comparisons, like joins and foreign keys
It is possible to apply Batched Nested Loop but with additional code that checks the range of the outer bigint and compare it only if it matches the range of integer. This has been added in YugabyteDB 2.21 with #20715 YSQL: Allow BNL on joins over different integer types to help migrations from PostgreSQL with such datatype inconsistencies.
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Jonathan Katz: Thoughts on PostgreSQL in 2024
It can be done like https://github.com/yugabyte/yugabyte-db/ has.
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Is co-partition or interleave necessary in Distributed SQL?
Therefore, interleaving or co-partitioning is probably not necessary, and would reduce agility and scalability more than improving the performance. Unless you have a good reason for it that you can share on Issue #79. But, first, test and tune the queries to see if you need something else.
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PostGIS on YugabyteDB Alma8 (workarounds)
This is a workaround, not supported. I've opened the following issue to get it solve in the YugabyteDB deployment: https://github.com/yugabyte/yugabyte-db/issues/19389
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Bitmap Scan in YugabyteDB
Note that there may still be a need for bitmaps, especially with disjunctions (OR) as the following is about conjunction (AND), and it can still be implemented, differently than PostgreSQL. This is tracked by #4634.
- Yugabyte – distributed PostgreSQL, 100% open source
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PL/Python on YugabyteDB
FROM almalinux:8 as build RUN dnf -y update &&\ dnf groupinstall -y 'Development Tools' # get YugabyteDB sources ARG YB_TAG=2.18 RUN git clone --branch ${YB_TAG} https://github.com/yugabyte/yugabyte-db.git WORKDIR yugabyte-db # install dependencies and compilation tools RUN dnf install -y https://dl.fedoraproject.org/pub/epel/epel-release-latest-8.noarch.rpm RUN dnf -y install epel-release libatomic rsync python3-devel cmake3 java-1.8.0-openjdk maven npm golang gcc-toolset-12 gcc-toolset-12-libatomic-devel patchelf glibc-langpack-en ccache vim wget python3.11-devel python3.11-pip clang ncurses-devel readline-devel libsqlite3x-devel RUN mkdir /opt/yb-build RUN chown "$USER" /opt/yb-build # Install Python 3 RUN alternatives --remove-all python3 RUN alternatives --remove-all python RUN alternatives --install /usr/bin/python python /usr/bin/python3.11 3 RUN alternatives --install /usr/bin/python3 python3 /usr/bin/python3.11 3 # add #include "pg_yb_utils.h" to src/postgres/src/pl/plpython/plpy_procedure.c RUN sed -e '/#include "postgres.h"/a#include "pg_yb_utils.h"' -i src/postgres/src/pl/plpython/plpy_procedure.c # if using python > 3.9 remove #include and #include from src/postgres/src/pl/plpython/plpython.h RUN sed -e '/#include /d' -e '/#include /d' -i src/postgres/src/pl/plpython/plpython.h # add '--with-python', to python/yugabyte/build_postgres.py under the configure_postgres method RUN sed -e "/'\.\/configure',/a\ '--with-python'," -i python/yugabyte/build_postgres.py # Build and package the release RUN YB_CCACHE_DIR="$HOME/.cache/yb_ccache" ./yb_build.sh -j$(nproc) --clean-all --build-yugabyted-ui --no-linuxbrew --clang15 -f release RUN chmod +x bin/get_clients.sh bin/parse_contention.py bin/yb-check-consistency.py RUN YB_USE_LINUXBREW=0 ./yb_release --force WORKDIR / RUN mv /yugabyte-db/build/yugabyte*.tar.gz /yugabyte.tgz
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YugabyteDB official Dockerfile
You have seen me using the official YugabyteDB Docker image extensively. This image is suitable for various purposes, including labs, development, testing, and even production. In the past, we used to create it internally due to its seamless integration with our build process. However, some companies prefer to construct the image on their own, which is indeed a commendable practice. After all, it's not advisable to run random images with root privileges on your servers. As a result, we have made a significant alteration by introducing a refined Dockerfile to our Github repository.
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FlameGraphs on Steroids with profiler.firefox.com
Of course, I can guess from the function names, but YugabyteDB is Open Source and I can search for them. What happens here is that I didn't declare a Primary Key for my table and then an internal one (ybctid) is generated, because secondary indexes need a key to address the table row. This ID generation calls /dev/urandom. I made this simple example to show that low-level traces can give a clue about high level data model problems.
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Understand what you run before publishing your (silly) benchmark results
To show that it is not difficut to understand what you run, when in a PostgreSQL-compatible database, I'll look at the HammerDB benchmark connected to YugabyteDB. HammerDB has no specific code for it but YugabyteDB is PostgreSQL-compatible (it uses PostgreSQL code on top of distributed storage and transaction).
pev2
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Retrieving the latest row per group from PostgreSQL
This runs in about 250ms. Let's have a look at the explain plan to understand it better. To visualise it, I am using the excellent visualisation tool from Dalibo.
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Pg_hint_plan: Force PostgreSQL to execute query plans how you want
The PEV2 is open source and give you a good visualization. I never used this pgmustard to compare.
https://explain.dalibo.com/
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Efficient Database Queries in Rails: A Practical Approach
Visualize Your Plan: Visit explain.dalibo.com and paste the generated plan text and query. Then, hit Submit. The tool will generate a visualization of your query plan. Here's an example of the visualization for the fifth attempt version of the query from this post. It shows the different types of scans that were used and how the data gets combined. The duration of each operation is also shown:
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What's new in the Postgres 16 query planner (a.k.a. optimizer)
You can download the whole analyzer as a simple html file and use it this way. No need to obfuscate or sanitize anything at all.
https://github.com/dalibo/pev2
- Visualizing and understanding PostgreSQL EXPLAIN plans made easy
- Don't use DISTINCT as a "join-fixer"
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When should you use the IN instead of the OR operator in Postgres queries?
You might be interested in sites like https://explain.dalibo.com/ which make the output a bit nicer to read. I use these quite often to quickly identify bottlenecks.
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200 Web-Based, Must-Try Web Design and Development Tools
PostgreSQL Query Plan Analyzer and Visualizer
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Do you use pgAdmin? Why?
I didn’t know about pev2, interesting, checking it now. Did you integrate the component yourself or are you using this hosted page by them: https://explain.dalibo.com/?
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Tuning DB
IMO it‘s important to get started with indexing. Grab your most frequently used queries and run an EXPLAIN ANALYZE to identify the problems. This tool might help you to understand your execution plans. Once you identified your problems, you can build indexes and check again. Then you should regularly check if your indexes are used.
What are some alternatives?
citus - Distributed PostgreSQL as an extension
TypeORM - ORM for TypeScript and JavaScript. Supports MySQL, PostgreSQL, MariaDB, SQLite, MS SQL Server, Oracle, SAP Hana, WebSQL databases. Works in NodeJS, Browser, Ionic, Cordova and Electron platforms.
cockroach - CockroachDB - the open source, cloud-native distributed SQL database.
awesome-db-tools - Everything that makes working with databases easier
neon - Neon: Serverless Postgres. We separated storage and compute to offer autoscaling, branching, and bottomless storage.
hypopg - Hypothetical Indexes for PostgreSQL
psycopg2 - PostgreSQL database adapter for the Python programming language
pev - Postgres Explain Visualizer
realtime - Broadcast, Presence, and Postgres Changes via WebSockets
sysbench - Scriptable database and system performance benchmark
Apache AGE - Graph database optimized for fast analysis and real-time data processing. It is provided as an extension to PostgreSQL. [Moved to: https://github.com/apache/age]
octosql - OctoSQL is a query tool that allows you to join, analyse and transform data from multiple databases and file formats using SQL.