kdb-tree | in-memory kdb tree -

by peermaps JavaScript Version: 1.1.2 License: BSD-2-Clause

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | kdb-tree Summary

kdb-tree is a JavaScript library. kdb-tree has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can install using 'npm i kdb-tree' or download it from GitHub, npm.

in-memory kdb tree

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Quality

Security

License

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Support

kdb-tree has a low active ecosystem.

It has 46 star(s) with 4 fork(s). There are 5 watchers for this library.

It had no major release in the last 12 months.

There are 2 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of kdb-tree is 1.1.2

Quality

kdb-tree has 0 bugs and 0 code smells.

Security

kdb-tree has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

kdb-tree code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

kdb-tree is licensed under the BSD-2-Clause License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

kdb-tree releases are not available. You will need to build from source code and install.

Deployable package is available in npm.

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kdb-tree Key Features

No Key Features are available at this moment for kdb-tree.

kdb-tree Examples and Code Snippets

No Code Snippets are available at this moment for kdb-tree.

Community Discussions

Trending Discussions on kdb-tree

How to import data from MySQL to HDFS and split/partition/distribute data by foreign key relations?

QUESTION

How to import data from MySQL to HDFS and split/partition/distribute data by foreign key relations?

Asked 2019-Jun-28 at 13:49

I am new to HDFS and Spark. I have input data for some simulations that is specific to regions (might be a country or part of country) and a function of time.

Lets assume I have following tables:

...

ANSWER

Answered 2019-Jun-27 at 14:31

sqoop (is not Spark) is more so for tables. It can use views but it was stated that for complex views the results may even be unreliable. So, that avenue is closed.

You will need to use a spark.read JDBC connection with a view in mySQL that uses region_id as key for distribution - for your parallelism - using the numPartitions approach defined on a "driving" table. The join with the other tables needs to rely on the mySQL engine.

I am not privy to your processing, but it seems hard to enforce a 1 to 1 region_id to partition approach. Moreover, more than 1 partition may exist on the same node - but independently.

You could get all tables independently and then JOIN, but there would be shuffling as there is no way to guarantee all individual READ's results would end up on same Node.

Source https://stackoverflow.com/questions/56790657

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install kdb-tree

You can install using 'npm i kdb-tree' or download it from GitHub, npm.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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