SparkStreaming | Spark

by ljcan Java Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(5)Vulnerabilities Install Support

kandi X-RAY | SparkStreaming Summary

SparkStreaming is a Java library typically used in Big Data, Kafka, Spark, Hadoop applications. SparkStreaming has no bugs, it has no vulnerabilities and it has low support. However SparkStreaming build file is not available. You can download it from GitHub.

Spark Streaming+Flume+Kafka+HBase+Hadoop+Zookeeper实现实时日志分析统计；SpringBoot+Echarts实现数据可视化展示

Support

Quality

Security

License

Reuse

Support

SparkStreaming has a low active ecosystem.

It has 461 star(s) with 256 fork(s). There are 27 watchers for this library.

It had no major release in the last 6 months.

SparkStreaming has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of SparkStreaming is current.

Quality

SparkStreaming has 0 bugs and 0 code smells.

Security

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

SparkStreaming code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

SparkStreaming 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

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

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

SparkStreaming saves you 662 person hours of effort in developing the same functionality from scratch.

It has 1536 lines of code, 61 functions and 38 files.

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

Top functions reviewed by kandi - BETA

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

Search for the course
Set the name
Returns the string representation of this class
Sets the current value
Query for Course count
Gets the property name
Simple test
Get the number of rows in the table
Get the singleton instance
The main entry point
Get the number of rows in the table
Get the singleton instance
Search for all search results
Query the list of Course
Query for total number of rows
Query for the course search count
Get table
Main loop
Creates a consumer
Put table
Runs the message loop
Main launcher

Get all kandi verified functions for this library.

SparkStreaming Key Features

No Key Features are available at this moment for SparkStreaming.

SparkStreaming Examples and Code Snippets

No Code Snippets are available at this moment for SparkStreaming.

Community Discussions

Trending Discussions on SparkStreaming

Spark: Exception in thread "main" java.lang.NoClassDefFoundError: org/apache/spark/Logging

Send data to Kafka topics based on a condition in Dataframe

Pause and resume KafkaConsumer in SparkStreaming

How do I serialize org.joda.time.DateTime in Spark Streaming using Scala?

py4j.protocol.Py4JavaError: An error occured while calling o22.start

QUESTION

Spark: Exception in thread "main" java.lang.NoClassDefFoundError: org/apache/spark/Logging

Asked 2021-Apr-30 at 13:18

I get this error when I run the code below

...

ANSWER

Answered 2021-Apr-29 at 05:13

Your scala version is 2.12, but you're referencing the spark-streaming-twitter_2.11 library which is built on scala 2.11. Scala 2.11 and 2.12 are incompatible, and that's what's giving you this error.

If you want to use Spark 3, you'd have to use a different dependency that supports scala 2.12.

Source https://stackoverflow.com/questions/67309310

QUESTION

Send data to Kafka topics based on a condition in Dataframe

Asked 2021-Mar-05 at 07:55

I want to change the Kafka topic destination to save the data depending on the value of the data in SparkStreaming. Is it possible to do so again? When I tried the following code, it only executes the first one, but does not execute the lower process.

...

ANSWER

Answered 2021-Mar-05 at 06:26

With the latest versions of Spark, you could just create a column topic in your dataframe which is used to direct the record into the corresponding topic.

In your case it would mean you can do something like

Source https://stackoverflow.com/questions/66485979

QUESTION

Pause and resume KafkaConsumer in SparkStreaming

Asked 2020-Jun-18 at 10:22

I've ended myself in a (strange) situation where, briefly, I don't want to consume any new record from Kafka, so pause the sparkStreaming consumption (InputDStream[ConsumerRecord]) for all partitions in the topic, do some operations and finally, resume consuming records.

First of all... is this possible?

I've been trying sth like this:

...

ANSWER

Answered 2020-Jun-18 at 10:22

Yes it is possible Add check pointing in your code and pass persistent storage (local disk,S3,HDFS) path

and whenever you start/resume your job it will pickup the Kafka Consumer group info with consumer offsets from the check pointing and start processing from where it was stopped.

Source https://stackoverflow.com/questions/62434153

QUESTION

How do I serialize org.joda.time.DateTime in Spark Streaming using Scala?

Asked 2020-Jun-17 at 09:49

I created a DummySource that reads lines from a file and convert it to TaxiRide objects. The problem is that there are fields that correspond to org.joda.time.DateTime where I use org.joda.time.format.{DateTimeFormat, DateTimeFormatter} and SparkStreaming cannot serialize those fields.

How do I make SparkStreaming serialize them? My code is below together with the error.

...

ANSWER

Answered 2020-Jun-17 at 09:49

AFAIK you cant serialize it

Best option is to create it as a Constant

Source https://stackoverflow.com/questions/62426017

QUESTION

py4j.protocol.Py4JavaError: An error occured while calling o22.start

Asked 2020-May-24 at 07:54

I am now trying to put SparkStreaming and Kafka work together on Ubantu. But here comes the question.

I can make sure Kafka's working properly.

On the first terminal:

...

ANSWER

Answered 2020-May-24 at 07:54

You forgot to add () in counts.pprint function.

Change counts.pprint to counts.pprint(), It will work.

Source https://stackoverflow.com/questions/61981379

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

Vulnerabilities

No vulnerabilities reported

Install SparkStreaming

You can download it from GitHub.
You can use SparkStreaming 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 SparkStreaming 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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