log_analytics_mapreduce | Analytics on top of http webserver log events
kandi X-RAY | log_analytics_mapreduce Summary
kandi X-RAY | log_analytics_mapreduce Summary
log_analytics_mapreduce is a Java library. log_analytics_mapreduce has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.
Analytics on top of http webserver log events using mapreduce
Analytics on top of http webserver log events using mapreduce
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Quality
Security
License
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Support
log_analytics_mapreduce has a low active ecosystem.
It has 5 star(s) with 6 fork(s). There are 4 watchers for this library.
It had no major release in the last 6 months.
log_analytics_mapreduce has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of log_analytics_mapreduce is current.
Quality
log_analytics_mapreduce has 0 bugs and 0 code smells.
Security
log_analytics_mapreduce has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
log_analytics_mapreduce code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
log_analytics_mapreduce does not have a standard license declared.
Check the repository for any license declaration and review the terms closely.
Without a license, all rights are reserved, and you cannot use the library in your applications.
Reuse
log_analytics_mapreduce releases are not available. You will need to build from source code and install.
Build file is available. You can build the component from source.
log_analytics_mapreduce saves you 360 person hours of effort in developing the same functionality from scratch.
It has 860 lines of code, 50 functions and 26 files.
It has low code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed log_analytics_mapreduce and discovered the below as its top functions. This is intended to give you an instant insight into log_analytics_mapreduce implemented functionality, and help decide if they suit your requirements.
- Runs a custom log analysis
- Maps the given value to the context
- The main entry point
- Maps a string value to the output stream
- Read lines from input split
- Main entry point
- Reduces the values of the given collection
- Get the partition number
- Reduces the values by key
- Maps an HTTP value to the context
- Reads the Geoip file
- Compute the partition number
- Maps the specified key to the context
- De - serialize the input data
- Writes the Http log
- Reduce values
- Writes the JSON data to the output
- The driver
- The driver status counter
- Demonstrates how to run the job size hits
- Runs the job size aggregator
- Writes the data to the output
Get all kandi verified functions for this library.
log_analytics_mapreduce Key Features
No Key Features are available at this moment for log_analytics_mapreduce.
log_analytics_mapreduce Examples and Code Snippets
No Code Snippets are available at this moment for log_analytics_mapreduce.
Community Discussions
No Community Discussions are available at this moment for log_analytics_mapreduce.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install log_analytics_mapreduce
You can download it from GitHub.
You can use log_analytics_mapreduce 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 log_analytics_mapreduce 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 .
You can use log_analytics_mapreduce 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 log_analytics_mapreduce 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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