kafka-clickstream-enrich | Kafka Streams Example - Joining streams

by gwenshap Java Version: Current License: No License

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

kandi X-RAY | kafka-clickstream-enrich Summary

kafka-clickstream-enrich is a Java library typically used in Big Data, Spark, JavaFX applications. kafka-clickstream-enrich has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

This example takes 2 streams of data: Stream of searches and stream of user clicks It also takes a stream of profile-updates, representing changes to a profiles table (assume we are getting those changes from MySQL using KafkaConnect connector). It joins those activity streams together, to generate an holistic view of user activity. The results show you, in one record the user's location, interests, what they searched for and what they ended up clicking. Providing rich source of data for analysis - which products are more desirable for which audience? "users who searched for this also looked at..." and other data products. This example makes use of the unique windowed-join, allowing us to match clicks with the search that happened in the same time window - in order to generate relevant results.

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Support

kafka-clickstream-enrich has a low active ecosystem.

It has 29 star(s) with 17 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 1322 days. There are 2 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of kafka-clickstream-enrich is current.

Quality

kafka-clickstream-enrich has 0 bugs and 0 code smells.

Security

kafka-clickstream-enrich has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

kafka-clickstream-enrich code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

kafka-clickstream-enrich 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

kafka-clickstream-enrich 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.

kafka-clickstream-enrich saves you 153 person hours of effort in developing the same functionality from scratch.

It has 382 lines of code, 33 functions and 12 files.

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

Top functions reviewed by kandi - BETA

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

Main method
Updates the user profile with the specified zipcode and interests
Gets the user ID
Entry point for the demo
Deserialize a string into an object
Closes the serializer
Configures the serializer with the given configs
Configure the deserialized class
Serialize to JSON

Get all kandi verified functions for this library.

kafka-clickstream-enrich Key Features

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kafka-clickstream-enrich Examples and Code Snippets

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Community Discussions

Trending Discussions on kafka-clickstream-enrich

How long is the data in KTable stored?

What is the difference between implementing Deserializer and Serde in Kafka Consumer API?

QUESTION

How long is the data in KTable stored?

Asked 2019-Nov-09 at 10:41

This as reference, stream of profile updates stored in KTable object.

How long this data will be stored in KTable object?
Let say we run multiple instance of application. And somehow, an instance crash. How about KTable data belong to that instance? Is it will be "recovered" by another instance?

I am thinking about storing update of data that rarely updated. So if an instance crash and another instance will be build those data from scratch again, it is possible they will never get thos data again. Because they never be streamed again, or easy saying, very rarely.

...

ANSWER

Answered 2019-Nov-08 at 13:00

The KTable is backed by a topic, so it would determine on what its retention + cleanup policies are.

If the cleanup policy is compact, then each unique key is stored "forever", or until the broker runs out of space, whichever is sooner.

If you run multiple instances, then each KTable will hold onto a subset of data from the partitions it consumed from, each table will not have all the data.

If any instance crashes, it will need to read all data from the beginning of its changelog topic, but you can configure standby replicas to account for that scenario

More info at https://cwiki.apache.org/confluence/display/KAFKA/Kafka+Streams+Internal+Data+Management

Source https://stackoverflow.com/questions/58763708

QUESTION

What is the difference between implementing Deserializer and Serde in Kafka Consumer API?

Asked 2019-Jun-04 at 13:51

I try to simulate Gwen (Chen) Shapira's kafka-clickstream-enrich kafka-stream project on GitHub (https://github.com/onurtokat/kafka-clickstream-enrich). When I consume a topic using consumer class using Deserializers, I encounter an error. The customized Serde class have serializer and deserializer. But, I try to understand why custom serde is used for deserializer, then consumer API gives error as it is not an instance of org.apache.kafka.common.serialization.Deserializer

The topic can be consumed using KTable with Serdes.Integer() Serializer and new ProfileSerde() Deserializer like below.

...

ANSWER

Answered 2019-May-24 at 15:32

Seems you misunderstood:

The topic can be consumed using KTable with Serdes.Integer() Serializer and new ProfileSerde() Deserializer like below.

you have to provide Consumed.with() with KeySerde and ValueSerde.

Regarding the Exception:

it's pretty clear - you have to set an implementation of Deserializer (not Serde)

Source https://stackoverflow.com/questions/56292702

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

Vulnerabilities

No vulnerabilities reported

Install kafka-clickstream-enrich

You can download it from GitHub.
You can use kafka-clickstream-enrich 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 kafka-clickstream-enrich 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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