yugabyte-db
xxHash
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yugabyte-db | xxHash | |
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87 | 28 | |
8,486 | 8,462 | |
1.3% | - | |
10.0 | 8.4 | |
2 days ago | 4 days ago | |
C | C | |
GNU General Public License v3.0 or later | GNU General Public License v3.0 or later |
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).
xxHash
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The One Billion Row Challenge in CUDA: from 17 minutes to 17 seconds
> GPU Hash Table?
How bad would performance have suffered if you sha256'd the lines to build the map? I'm going to guess "badly"?
Maybe something like this in CUDA: https://github.com/Cyan4973/xxHash ?
- ETag and HTTP Caching
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Day 64: Implementing a basic Bloom Filter Using Java BitSet api
Examples of fast, simple hashes that are independent enough includes murmur, xxHash, Fowler–Noll–Vo hash function and many others
- Closed-addressing hashtables implementation
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NIST Retires SHA-1 Cryptographic Algorithm
If you're only using the hash for non-cryptographic applications, there are much faster hashes: https://github.com/Cyan4973/xxHash
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Does the checksum algorithm crc32c-intel support AMD Ryzen series 3000 or newer?
I found the benchmark result of AMD ryzen 5950X
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[Study Project] A memory-optimized JSON data structure
But what's the catch, you're thinking ? Well, it is a bit slower than its counterparts when it comes to deserializing (and marginally faster for serializing). To achieve smaller footprint, it uses a few tricks and notably a custom hash table to deduplicate strings. This comes at a cost of course (even when featuring xxHash to speed things up), but keeps the slowdown reasonable (I think).
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What do you typically use for non-cryptographic hash functions?
Non cryptographic hashes has collisions, for example, assume you having content like "abcdefg" which hashed value is "123", in case of weak hash algorithm some other content like "abcdefZ" can also have a hash "123" which basically means such hash function is failed to be unique fingerprint of particular content. BLAKE3 for example can do 6-7Gb/s which make it pretty fast and secure. If your requirement accepts collision with defined error rate, I would advise you to take a look at XXH3 if you need very snappy hash algorithm, which can run at pace or RAM access (30GB/s+), but again, run tests at particular equipment you targeting, may be AES hardware accelerated MeowHash will serve you better.
- C++ gonna die😥
- rsync, article 3: How does rsync work?
What are some alternatives?
citus - Distributed PostgreSQL as an extension
BLAKE3 - the official Rust and C implementations of the BLAKE3 cryptographic hash function
cockroach - CockroachDB - the open source, cloud-native distributed SQL database.
meow_hash - Official version of the Meow hash, an extremely fast level 1 hash
neon - Neon: Serverless Postgres. We separated storage and compute to offer autoscaling, branching, and bottomless storage.
xxh - 🚀 Bring your favorite shell wherever you go through the ssh. Xonsh shell, fish, zsh, osquery and so on.
psycopg2 - PostgreSQL database adapter for the Python programming language
blake3 - An AVX-512 accelerated implementation of the BLAKE3 cryptographic hash function
realtime - Broadcast, Presence, and Postgres Changes via WebSockets
smhasher - Hash function quality and speed tests
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]
swift-crypto - Open-source implementation of a substantial portion of the API of Apple CryptoKit suitable for use on Linux platforms.