sparkMeasure
This is the development repository for sparkMeasure, a tool and library designed for efficient analysis and troubleshooting of Apache Spark jobs. It focuses on easing the collection and examination of Spark metrics, making it a practical choice for both developers and data engineers. (by LucaCanali)
dblink
Distributed Bayesian Entity Resolution in Apache Spark (by cleanzr)
| sparkMeasure | dblink | |
|---|---|---|
| 1 | 1 | |
| 742 | 57 | |
| 1.9% | - | |
| 5.6 | 0.0 | |
| 12 days ago | almost 4 years ago | |
| Scala | Scala | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.
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.
sparkMeasure
Posts with mentions or reviews of sparkMeasure.
We have used some of these posts to build our list of alternatives
and similar projects.
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Spark Write Metrics
As an alternative to other proposed solutions, you could try and leverage the Spark metrics system to extract this information from accumulators. Metrics include total records and bytes written at each stage, among others. Take a look at SparkMeasure as well as an implementation example if you need to roll your own.
dblink
Posts with mentions or reviews of dblink.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2021-03-10.
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[D] Machine Learning and "Record Linkage"
Felligi-Sunter is the baseline model in record linkage research. It is implemented in R in fastLink and RecordLinkage, but you will need training data. There are some other options, e.g. dblink, that use Bayesian methods and a latent variable set up so you don’t need training data.
What are some alternatives?
When comparing sparkMeasure and dblink you can also consider the following projects:
delight - A Spark UI and Spark History Server alternative with CPU and Memory metrics! Delight is free, cross-platform, and open-source.
mmlspark - Simple and Distributed Machine Learning [Moved to: https://github.com/microsoft/SynapseML]
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
entity-embed - PyTorch library for transforming entities like companies, products, etc. into vectors to support scalable Record Linkage / Entity Resolution using Approximate Nearest Neighbors.
Spark Tools - Executable Apache Spark Tools: Format Converter & SQL Processor
splink - Fast, accurate and scalable probabilistic data linkage with support for multiple SQL backends