spark | Lightning-fast cluster computing in Java , Scala and Python

 by   mesos Scala Version: v0.7.3 License: No License

kandi X-RAY | spark Summary

kandi X-RAY | spark Summary

spark is a Scala library typically used in Big Data, Spark applications. spark has no bugs and it has medium support. However spark has 3 vulnerabilities. You can download it from GitHub.

Apache Spark is now an incubator Apache project, and we've moved the codebase.
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              spark has a medium active ecosystem.
              It has 1423 star(s) with 389 fork(s). There are 199 watchers for this library.
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              It had no major release in the last 6 months.
              spark has no issues reported. There are 13 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of spark is v0.7.3

            kandi-Quality Quality

              spark has no bugs reported.

            kandi-Security Security

              spark has 3 vulnerability issues reported (1 critical, 1 high, 1 medium, 0 low).

            kandi-License License

              spark does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
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              Without a license, all rights are reserved, and you cannot use the library in your applications.

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              spark releases are not available. You will need to build from source code and install.
              Installation instructions are not available. Examples and code snippets are available.

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            spark Key Features

            No Key Features are available at this moment for spark.

            spark Examples and Code Snippets

            No Code Snippets are available at this moment for spark.

            Community Discussions

            QUESTION

            Scala: in where clause how to get column string value and split, and intersect against another array?
            Asked 2021-Jun-15 at 20:34

            I have a dataframe where one column is ; separated strings, e.g. "str1;str2;str3;str4", I also have another static list "strx;stry;strz", the goal is to split the column string value and check if the split array has any intersection with the static list, and keep that row

            I tried

            ...

            ANSWER

            Answered 2021-Jun-15 at 20:34

            It seems you're mixing up Spark's split method for Columns with Scala's split for Strings. Please see example below for how the two different split methods are used. Method array_intersect is for intersecting the split Array column with the split element-filter string.

            Source https://stackoverflow.com/questions/67977336

            QUESTION

            Why does Spark perform an unnecessary shuffle during a joinWith on a pre-partitioned dataframe?
            Asked 2021-Jun-15 at 12:49

            This example has been tested with Spark 2.4.x. Let's consider 2 simple dataframes:

            ...

            ANSWER

            Answered 2021-Jun-15 at 12:49

            This seems like a bug introduced by a bug fix in this ticket. The result was wrong for outer joins. Hence the need to add a Project node (packing of the struct) before the Join node.

            However, we end up with this kind of query plan:

            Source https://stackoverflow.com/questions/67400097

            QUESTION

            Java Spark Dataset MapFunction - Task not serializable without any reference to class
            Asked 2021-Jun-15 at 11:58

            I have a following class that reads csv data into Spark's Dataset. Everything works fine if I just simply read and return the data.

            However, if I apply a MapFunction to the data before returning from function, I get

            Exception in thread "main" org.apache.spark.SparkException: Task not serializable

            Caused by: java.io.NotSerializableException: com.Workflow.

            I know Spark's working and its need to serialize objects for distributed processing, however, I'm NOT using any reference to Workflow class in my mapping logic. I'm not calling any Workflow class function in my mapping logic. So why is Spark trying to serialize Workflow class? Any help will be appreciated.

            ...

            ANSWER

            Answered 2021-Feb-17 at 08:21

            you could make Workflow implement Serializeble and SparkSession as @transient

            Source https://stackoverflow.com/questions/66233112

            QUESTION

            I can't pass parameters to foreach loop while implementing Structured Streaming + Kafka in Spark SQL
            Asked 2021-Jun-15 at 04:42

            I followed the instructions at Structured Streaming + Kafka and built a program that receives data streams sent from kafka as input, when I receive the data stream I want to pass it to SparkSession variable to do some query work with Spark SQL, so I extend the ForeachWriter class again as follows:

            ...

            ANSWER

            Answered 2021-Jun-15 at 04:42

            do some query work with Spark SQL

            You wouldn't use a ForEachWriter for that

            Source https://stackoverflow.com/questions/67972167

            QUESTION

            Scala sortWith for java.sql.Timestamp sometimes will or won't compile when using two underscores
            Asked 2021-Jun-14 at 23:28

            I'm confused why a type that implements comparable isn't "implicitly comparable", and also why certain syntaxes of sortWith won't compile at all:

            ...

            ANSWER

            Answered 2021-Jun-11 at 10:35
            // Works but won't sort eq millis
            val records = iter.toArray.sortWith(_.event_time.getTime < _.event_time.getTime)
            

            Source https://stackoverflow.com/questions/67929439

            QUESTION

            PySpark Incremental Count on Condition
            Asked 2021-Jun-14 at 22:51

            Given a Spark dataframe with the following columns I am trying to construct an incremental/running count for each id based on when the contents of the event column evaluate to True.

            ...

            ANSWER

            Answered 2021-Jun-14 at 22:51

            You can use sum function, casting your event as an int:

            Source https://stackoverflow.com/questions/67977729

            QUESTION

            ScalaTest error object flatspec is not a member of package org.scalatest
            Asked 2021-Jun-14 at 17:36

            I have sample tests used from scalatest.org site and maven configuration again as mentioned in reference documents on scalatest.org, but whenever I run mvn clean install it throws the compile time error for scala test(s).

            Sharing the pom.xml below

            ...

            ANSWER

            Answered 2021-Jun-14 at 07:54

            You are using scalatest version 2.2.6:

            Source https://stackoverflow.com/questions/67958842

            QUESTION

            Cannot install additional requirements to apache airflow
            Asked 2021-Jun-14 at 16:35

            I am using the following docker-compose image, I got this image from: https://github.com/apache/airflow/blob/main/docs/apache-airflow/start/docker-compose.yaml

            ...

            ANSWER

            Answered 2021-Jun-14 at 16:35

            Support for _PIP_ADDITIONAL_REQUIREMENTS environment variable has not been released yet. It is only supported by the developer/unreleased version of the docker image. It is planned that this feature will be available in Airflow 2.1.1. For more information, see: Adding extra requirements for build and runtime of the PROD image.

            For the older version, you should build a new image and set this image in the docker-compose.yaml. To do this, you need to follow a few steps.

            1. Create a new Dockerfile with the following content:

            Source https://stackoverflow.com/questions/67851351

            QUESTION

            How to run a Spark-Scala unit test notebook in Databricks?
            Asked 2021-Jun-14 at 15:42

            I am trying to write a unit test code for my Spark-Scala notebook using scalatest.funsuite but the notebook with test() is not getting executed in databricks. Could you please let me know how can I run it?

            Here is the sample test code for the same.

            ...

            ANSWER

            Answered 2021-Jun-14 at 15:42

            You need to explicitly create the object for that test suite & execute it. In IDE you're relying on specific runner, but it doesn't work in the notebook environment.

            You can use either the .execute function of create object (docs):

            Source https://stackoverflow.com/questions/67971085

            QUESTION

            Does the number of kafka partitions increase the speed of Spark writing to kafka?
            Asked 2021-Jun-14 at 14:31

            When reading, Spark have a mapping 1:1 to kafka partitions, so, with more partitions we can leverage more parellelism to our job.

            But does it apply when Spark is writing in kafka ? Writing the same dataset in one topic with 4 partitions is more fast than writing in a topic with 1 partition ?

            ...

            ANSWER

            Answered 2021-Jun-14 at 14:31

            Yes.

            If your topic has 1 partition means it is in one broker. So, If you increase producer rate for the topic, then that broker becomes busy. But if you have multiple partitions, your Kafka cluster shared those partitions into different brokers and those production rate shared within multiple brokers. So, Writing the same dataset in one topic with 4 partitions is more fast than writing in a topic with 1 partition.

            This not only production rate. In Kafka brokers, There is multiple processes like compactions, compressions, segmentations etc... So with number of messages, that work load becomes high. But with multiple partitions in multiple brokers, it will be distributed.

            However, you don’t necessarily want to use more partitions than needed because increasing partition count simultaneously increases the number of open server files and leads to increased replication latency.

            from kafka documentation

            Distribution The partitions of the log are distributed over the servers in the Kafka cluster with each server handling data and requests for a share of the partitions. Each partition is replicated across a configurable number of servers for fault tolerance. Each partition has one server which acts as the "leader" and zero or more servers which act as "followers". The leader handles all read and write requests for the partition while the followers passively replicate the leader. If the leader fails, one of the followers will automatically become the new leader. Each server acts as a leader for some of its partitions and a follower for others so load is well balanced within the cluster.

            Source https://stackoverflow.com/questions/67971694

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

            Vulnerabilities

            No vulnerabilities reported

            Install spark

            You can download it from GitHub.

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