trident-tutorial | A practical Storm Trident tutorial | Learning library

by eshioji Java Version: Current License: Apache-2.0

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kandi X-RAY | trident-tutorial Summary

trident-tutorial is a Java library typically used in Tutorial, Learning, Pytorch, Fastapi applications. trident-tutorial 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.

A practical Storm Trident tutorial. This tutorial builds on [Pere Ferrera][1]'s excellent [material][2] for the [Trident hackaton@Big Data Beers #4 in Berlin][3]. The vagrant setup is based on Taylor Goetz’s [contribution][6]. The Hazelcast state code is based on wurstmeister’s [code][7]. [1]:[2]:[3]:[6]:[7]:Have a look at the accompanying [slides][4] as well.

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trident-tutorial has a low active ecosystem.

It has 121 star(s) with 58 fork(s). There are 15 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 1 have been closed. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of trident-tutorial is current.

Quality

trident-tutorial has no bugs reported.

Security

trident-tutorial has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

trident-tutorial 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

trident-tutorial 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.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Main test method
Throws a StormTopology
Emit followers
Classify followers
Retrieve the keywords from the given state
Search for a given keyword
Parses the tweet
Creates a status object from rawJSON string
Bulk indexing
Performs bulk index
Main method
Creates a topology from a pipeline spout
Main entry point
Creates a Storm topology
Launch the topology
Build topology
Runs a feeder
Only for testing
Executes multi get
Entry point of the topology
Test a Topology
Multi - put operations
Adds the current value to the specified map

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trident-tutorial Key Features

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trident-tutorial Examples and Code Snippets

No Code Snippets are available at this moment for trident-tutorial.

Community Discussions

Trending Discussions on trident-tutorial

What 's difference for the latency between Storm and Spark Streaming when dealing with tuples\messages?

QUESTION

What 's difference for the latency between Storm and Spark Streaming when dealing with tuples\messages?

Asked 2017-May-30 at 04:21

1,Based on the description below, Both Storm and Spark Streaming dealing with the messages/tuples in batch or small/micro batch? https://storm.apache.org/releases/2.0.0-SNAPSHOT/Trident-tutorial.html

2,If the answer for the above question is yes, it means both technologies have the delay when dealing with the messages/tuples ? If that's the case why I heard often that latency for the Storm is better then Spark Streaming ,such as the below article? https://www.ericsson.com/research-blog/data-knowledge/apache-storm-vs-spark-streaming/

3,From the Trident-tutorial it describes that : "Generally the size of those small batches will be on the order of thousands or millions of tuples, depending on your incoming throughput." So what's the really size of the small batch? thousands or millions of tuples?If it is , how Storm can keep the short latency?

https://storm.apache.org/releases/2.0.0-SNAPSHOT/Trident-tutorial.html

...

ANSWER

Answered 2017-May-30 at 04:21

Storm's core api tries to process an event as it arrives. Its an event at a time processing model which can result in very low latencies.

Storm's Trident is a micro batching model built on top of the storm's core apis for providing exactly-once guarantees. Spark streaming is also based on micro batching and comparable to trident in terms of latencies.

So if one is looking for extremely low latency processing Storm's core api would be the way to go. However this guarantees only at-least once processing and theres a chance of receiving duplicate events in case of failures and the application is expected to handle this.

Take a look at the streaming benchmark from yahoo [1], that can provide more insights.

[1] https://yahooeng.tumblr.com/post/135321837876/benchmarking-streaming-computation-engines-at

Source https://stackoverflow.com/questions/44233693

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

Vulnerabilities

No vulnerabilities reported

Install trident-tutorial

Build a job jar like so:.

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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