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Pandas
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peaks-framework
Discontinued The Peaks Consolidation is equipped with state-of-the-art algorithms and data structures that support high-performance databending exercises. It specializes in management accounting and consolidation, with some special topics in machine learning and bioinformatics. [Moved to: https://github.com/hkpeaks/peaks-consolidation]
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peaks-consolidation reviews and mentions
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Filter a 7 billion-row dataset using 32GB Memory
Script and Data
- Success in Lighting Fast Billion-Row Sorting Using a 32GB Desktop PC
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Stochastic Sublinear Streaming Algorithms
This streaming algorithms will support billion-row sorting
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Billion-row Sorting Scripts for Peaks, Polars, Pandas and DuckDB
Sample data for 100,000 rows
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Understand The SQL Execution Order
SplitFile2Folder: allows to filter a big CSV file or a folder which contains many CSV file to a folder/sub-folder which results many table partitions
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OrderBy{Ledger(A) Account(D) Quantity(FloatA) Part_No(A)}
Now I am upgrading the Peaks, not only support orderby, but also support billion-row sorting use cases using only 32GB memory.
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Success to Build 2 functions: SplitFile2Folder and FilterFromFolder
BillionRowsTestingLog is a set of processing logs included in the 1st pre-release delivery. These are foucs on billion-row databending exercises.
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Implement Go Streaming to Process Over Memory Size Dataset
I have decided to share my written algorithms for a period of time by spending additional time to maintain the repository.
- Solved to Filter/Summarize Data from Huge CSV Files
- Solved Huge CSV File
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A note from our sponsor - InfluxDB
www.influxdata.com | 1 May 2024
Stats
hkpeaks/peaks-consolidation is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of peaks-consolidation is Go.
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