kcache | An In-Memory Cache Backed by Apache Kafka | Pub Sub library

by rayokota Java Version: kcache-parent-5.0.0 License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | kcache Summary

kcache is a Java library typically used in Messaging, Pub Sub, Kafka applications. kcache has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub, Maven.

KCache is a client library that provides an in-memory cache backed by a compacted topic in Kafka. It is one of the patterns for using Kafka as a persistent store, as described by Jay Kreps in the article It's Okay to Store Data in Apache Kafka.

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Security

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Support

kcache has a low active ecosystem.

It has 217 star(s) with 32 fork(s). There are 10 watchers for this library.

It had no major release in the last 6 months.

There are 5 open issues and 22 have been closed. On average issues are closed in 22 days. There are 10 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of kcache is kcache-parent-5.0.0

Quality

kcache has 0 bugs and 0 code smells.

Security

kcache has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

kcache code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

kcache is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

kcache releases are not available. You will need to build from source code and install.

Deployable package is available in Maven.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

It has 9636 lines of code, 886 functions and 83 files.

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

Top functions reviewed by kandi - BETA

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

Initialize the cache
Verify if a topic exists
Read offsets from the local file
Creates a topic
Set up the cache
Create local cache
Bootstrapped broker endpoint
Writes offsets to a checkpoint file
Write a topic entry
Stores the value in the store
Places the given entries into the store
Returns a key value iterator
Places all of the specified entries in the store
Makes the next key
Creates a cache
Returns a key range iterator
Creates a flatMap iterator that maps the keys of the supplied key value using the supplied function
Creates the cache
Stores the value associated with the given key
Returns the next key
Open the database
Set up keys
Closes the database
Creates a key - value iterator
Returns all key values in the database
Opens the database

Get all kandi verified functions for this library.

kcache Key Features

No Key Features are available at this moment for kcache.

kcache Examples and Code Snippets

No Code Snippets are available at this moment for kcache.

Community Discussions

Trending Discussions on kcache

How to correctly assign double8 type

Python profiling, imports (and specially __init__) is what seems to take the most time

QUESTION

How to correctly assign double8 type

Asked 2019-Nov-15 at 14:47

I am trying to assign a double8 type, ultimately for some AVX2 parallelisation using pyopencl. I am making code to find the dot product efficiently between two vectors, va and vb, and return the result vc.

Code is below:

...

ANSWER

Answered 2019-Nov-15 at 14:47

I don't really know anything about pyopencl, but I assume the kernels are exactly like regular OpenCL kernels. Your problem isn't with assignment of a double8 type, rather the assignment of value vc. you have vc as a __global float*, a pointer type. See how you treated va & vb as arrays and accessed their elements with [index]? The same is true for vc.Since your vc is only intended to store a single value, you can do

vc[0] = ...

or a pointer derefrence

*cv = ...

So what you should do is this instead:

Source https://stackoverflow.com/questions/58877001

QUESTION

Python profiling, imports (and specially __init__) is what seems to take the most time

Asked 2018-May-27 at 17:27

I have a script that seemed to run slow and that i profiled using cProfile (and visualisation tool KCacheGrind)

It seems that what is taking almost 90% of the runtime is the import sequence, and especially the running of the _ _ init _ _.py files...

Here a screenshot of the KCacheGrind output (sorry for attaching an image...)

I am not very familiar with how the import sequence works in python ,so maybe i got something confused... I also placed _ _ init _ _.py files in everyone of my custom made packages, not sure if that was what i should have done.

Anyway, if anyone has any hint, greatly appreciated!

EDIT: additional picture when function are sorted by self:

EDIT2:

here the code attached, for more clarity for the answerers:

...

ANSWER

Answered 2018-May-27 at 17:27

No. You are conflating cumulative time with time spent in the top-level code of the __init__.py file itself. The top-level code calls other methods, and those together take a lot of time.

Look at the self column instead to find where all that time is being spent. Also see What is the difference between tottime and cumtime in a python script profiled with cProfile?, the incl. column is the cumulative time, self is the total time.

I'd just filter out all the entries; the Python project has already made sure those paths are optimised.

However, your second screenshot does show that in your profiling run, all that your Python code busied itself with was loading bytecode for modules to import (the marshal module provides the Python bytecode serialisation implementation). Either the Python program did nothing but import modules and no other work was done, or it is using some form of dynamic import that is loading a large number of modules or is otherwise ignoring the normal module caches and reloading the same module(s) repeatedly.

You can profile import times using Python 3.7's new -X importtime command-line switch, or you could use a dedicated import-profiler to find out why imports take such a long time.

Source https://stackoverflow.com/questions/50554374

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

Vulnerabilities

No vulnerabilities reported

Install kcache

You can download it from GitHub, Maven.
You can use kcache like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the kcache component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

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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