Red-Index | Auto-indexer of repositories and cogs

by Cog-Creators Python Version: Current License: GPL-3.0

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | Red-Index Summary

Red-Index is a Python library. Red-Index has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However Red-Index build file is not available. You can download it from GitHub.

Auto-indexer of repositories and cogs

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Red-Index has a low active ecosystem.

It has 25 star(s) with 46 fork(s). There are 6 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 4 have been closed. On average issues are closed in 70 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Red-Index is current.

Quality

Red-Index has 0 bugs and 0 code smells.

Security

Red-Index has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Red-Index code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Red-Index is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

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

Red-Index has no build file. You will be need to create the build yourself to build the component from source.

It has 247 lines of code, 16 functions and 2 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed Red-Index and discovered the below as its top functions. This is intended to give you an instant insight into Red-Index implemented functionality, and help decide if they suit your requirements.

Process all the cog
Read the info json
Check the cog package
Check repo info
Return sha1 hash of url
Make the error log for repos
Populates the list of cogs
Clean url
Return sha1 digest of url

Get all kandi verified functions for this library.

Red-Index Key Features

No Key Features are available at this moment for Red-Index.

Red-Index Examples and Code Snippets

No Code Snippets are available at this moment for Red-Index.

Community Discussions

Trending Discussions on Red-Index

Clustered indexes in Synapse Dedicated Pool and row storage

Structure of a Multi-column index in SQL server

Using clustered than non-clustered index with columns that include date and nvarchar(50)

QUESTION

Clustered indexes in Synapse Dedicated Pool and row storage

Asked 2021-May-05 at 14:50

I try to understand indexes in Azure Synapse and I'm a bit confused by some of them.

Regarding the Clustered Columnstore Index, I've a feeling that it works a bit like Apache Parquet, with row groups and column chunks inside. In heap tables the data is not indexed, so it seems pretty clear too.

But what about the clustered and nonclustered indexes? The documentation defines them as:

Clustered indexes may outperform clustered columnstore tables when a single row needs to be quickly retrieved. For queries where a single or very few row lookup is required to perform with extreme speed, consider a clustered index or nonclustered secondary index. The disadvantage to using a clustered index is that only queries that benefit are the ones that use a highly selective filter on the clustered index column. To improve filter on other columns, a nonclustered index can be added to other columns. However, each index that is added to a table adds both space and processing time to loads.

Here are my questions:

Does it mean they're more like the indexes from SQL Server? I mean, the clustered index would order the data by one column and store it as rows? And the non clustered would be an extra sorted index storing only references to the rows?
If my assumption about row-based format is correct, does it mean the clustered index is not performant for the analytical queries, doesn't it?
What happens if we create a table with both Columnstore and Clustered Indexes? The data is duplicated, once for the columnar format, once for the row format?

Some links I found on that topic, but still have some doubts whether they apply to Synapse:

...

ANSWER

Answered 2021-May-05 at 14:50

Bartosz,

Does it mean they're more like the indexes from SQL Server? I mean, the clustered index would order the data by one column and store it as rows? And the non clustered would be an extra sorted index storing only references to the rows?

You are correct on clustering and non clustering definition - with a slight twist. It is similar to traditional SQL Server and that the leaf of cluster is the actual data row. In summary, the physical organization of data rows for Synapse/pdw will be

Clustered columnstore - data is not sorted and row segments can have overlapping min-max values
Clustered columstore with order by - data is sorted, hence the row segments will not have overlapps and skipping will optimal
Heap - which is row format
Clustered index this is SQL Server clustered index where lead/data portion is sorted.

If my assumption about row-based format is correct, does it mean the clustered index is not performant for the analytical queries, doesn't it?

Clustered index will be performant if your query selects a set of values are sequential. for example - select * from table where year between 2005 and 2007. Row/Heap tables are efficient if your projection/select includes all or most of the columns of the table. Columnstore organization is efficient if have wide tables and select a handful of columns.

What happens if we create a table with both Columnstore and Clustered Indexes? The data is duplicated, once for the columnar format, once for the row format? If you have a columstore index, you wont be able to create a clustered index.

Source https://stackoverflow.com/questions/67218324

QUESTION

Structure of a Multi-column index in SQL server

Asked 2020-Jul-22 at 00:33

Where can I find a good representation of the of how data is stored in pages and how the B tree is constructed for a multi-column index (specifically for SQL server, but not necessarily)?

I'm referring to something like what you see in https://docs.microsoft.com/en-us/sql/relational-databases/reading-pages?view=sql-server-ver15 (for single column) but extended for multi-columns.

Another example for single column index:

https://www.sqlshack.com/clustered-index-vs-heap/

Thanks.

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ANSWER

Answered 2020-Jul-21 at 12:49

The index key values are sorted first by the first key column, then by the second key column, and then yt's exactly the same, except with additional columns on the non-leaf nodes. So if the first key column is a number, and the second the name of an animal, the non-leaf pages might have ranges like:

Source https://stackoverflow.com/questions/63014764

QUESTION

Using clustered than non-clustered index with columns that include date and nvarchar(50)

Asked 2020-Jun-07 at 13:16

I have a table called 'GameTransactions'. It is critical for the table to work well in terms of performance (The table will have millions of records when the site is going to be operational). I thought to index it. The columns that I used for the columns are:

...

ANSWER

Answered 2020-Jun-07 at 10:55

Use EXISTS instead of COUNT to conditionally insert the row. This will be more efficient since a count is not needed. Make sure the index is unique to ensure duplicates are not possible.

Use >= instead of > for the timestamp criteria so that 2 sessions with the same timestamp don't both insert the same row, although one would err if a unique index or constraint exists.

Furthermore, consider removing NOLOCK to ensure concurrent sessions don't insert rows for the same UserID/TransactionID/ProviderID withing the TransactionTimeStamp date range. I suggest SERIALIZABLE for this purpose. Example DDL below with the query encapsulated in a stored procedure below, leveraging the primary key index for both performance and data integrity.

Source https://stackoverflow.com/questions/62243329

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

Vulnerabilities

No vulnerabilities reported

Install Red-Index

You can download it from GitHub.
You can use Red-Index like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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