Partition management extension for PostgreSQL
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Updated
Nov 7, 2024 - PLpgSQL
Partition management extension for PostgreSQL
MapReduce, Spark, Java, and Scala for Data Algorithms Book
A scikit-learn based module for multi-label et. al. classification
Official PyTorch implementation of Superpoint Transformer introduced in [ICCV'23] "Efficient 3D Semantic Segmentation with Superpoint Transformer" and SuperCluster introduced in [3DV'24 Oral] "Scalable 3D Panoptic Segmentation As Superpoint Graph Clustering"
Partitioning tool for PostgreSQL
ActiveRecord PostgreSQL Partitioning
Header-Only C++ Library for Graph Representation and Algorithms
KaHyPar (Karlsruhe Hypergraph Partitioning) is a multilevel hypergraph partitioning framework providing direct k-way and recursive bisection based partitioning algorithms that compute solutions of very high quality.
KaHIP -- Karlsruhe HIGH Quality Partitioning.
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Mt-KaHyPar (Multi-Threaded Karlsruhe Hypergraph Partitioner) is a shared-memory multilevel graph and hypergraph partitioner equipped with parallel implementations of techniques used in the best sequential partitioning algorithms. Mt-KaHyPar can partition extremely large hypergraphs very fast and with high quality.
A node js library with a distributed leader/follower algorithm ready to be used
PySpark Algorithms Book: https://www.amazon.com/dp/B07X4B2218/ref=sr_1_2
A Django extension that supports PostgreSQL 11 time ranges and list partitioning.
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