spark-test | Allows testing Spark Web Framework based applications

 by   despegar Java Version: 1.1.8 License: Apache-2.0

kandi X-RAY | spark-test Summary

kandi X-RAY | spark-test Summary

spark-test is a Java library typically used in Big Data, Spark applications. spark-test 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, Maven.

Allows testing Spark Web Framework based applications through HTTP

            kandi-support Support

              spark-test has a low active ecosystem.
              It has 31 star(s) with 9 fork(s). There are 11 watchers for this library.
              It had no major release in the last 12 months.
              There are 7 open issues and 5 have been closed. On average issues are closed in 17 days. There are 1 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of spark-test is 1.1.8

            kandi-Quality Quality

              spark-test has 0 bugs and 7 code smells.

            kandi-Security Security

              spark-test has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              spark-test code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              spark-test 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.

            kandi-Reuse Reuse

              spark-test releases are not available. You will need to build from source code and install.
              Deployable package is available in Maven.
              Build file is available. You can build the component from source.
              Installation instructions are not available. Examples and code snippets are available.
              spark-test saves you 112 person hours of effort in developing the same functionality from scratch.
              It has 284 lines of code, 19 functions and 4 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

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            spark-test Key Features

            No Key Features are available at this moment for spark-test.

            spark-test Examples and Code Snippets

            No Code Snippets are available at this moment for spark-test.

            Community Discussions


            How to reference a project definition in a parent build.sbt file?
            Asked 2022-Feb-27 at 18:25

            I'm playing around with the scala-forklift library and wanted to test an idea by modifying the code in the library and example project.

            This is how the project is structured:

            • /build.sbt -> Contains definition of scala-forklift-slick project (including its dependencies) in the form of:


            Answered 2022-Feb-27 at 18:25

            Luis Miguel Mejía Suárez's comment worked perfectly and was the easier approach.

            In the context of this project, all I had to do was:

            1. Append -SNAPSHOT to the version in /version.sbt (should not be needed normally but for this project I had to do this)
            2. Run sbt publishLocal in the parent project.

            After this, the example project (which already targets the -SNAPSHOT version) is able to pick up the locally built package.



            PySpark doesn't find Kafka source
            Asked 2022-Jan-24 at 23:36

            I am trying to deploy a docker container with Kafka and Spark and would like to read to Kafka Topic from a pyspark application. Kafka is working and I can write to a topic and also spark is working. But when I try to read the Kafka stream I get the error message:



            Answered 2022-Jan-24 at 23:36

            Missing application resource

            This implies you're running the code using python rather than spark-submit

            I was able to reproduce the error by copying your environment, as well as using findspark, it seems PYSPARK_SUBMIT_ARGS aren't working in that container, even though the variable does get loaded...

            The workaround would be to pass the argument at execution time.



            Intellij Idea Code Coverage Vs Maven Jacoco
            Asked 2021-Mar-10 at 21:45

            when I run my tests in Intellij idea choosing code coverage tool as JaCoCo and include my packages I see I get 80% above coverage in the report but when I run it using maven command line I get 0% in JaCoCo report below are two questions.

            1. can I see what command Intellij Idea Ultimate version is using to run my unit tests with code coverage ?

            2. Why my maven command mvn clean test jacoco:report is showing my coverage percentage as 0%.

            This is a Scala maven project.

            My POM.xml file:-



            Answered 2021-Feb-03 at 22:16

            Assuming that you are using JaCoCo with cobertura coverage you need to declare the dependencies and the plugin to run the command mvn cobertura:cobertura.



            Upgraded the spark version, and during spark jobs encountering java.lang.NoSuchMethodError: scala.Product.$init$(Lscala/Product;)V
            Asked 2020-Oct-08 at 20:51

            We recently made an upgrade from Spark 2.4.2 to 2.4.5 for our ETL project.

            After deploying the changes, and running the job I am seeing the following error:



            Answered 2020-Oct-08 at 20:51

            I think it is due to mismatch between Scala version with which the code is compiled and Scala version of the runtime.

            Spark 2.4.2 was prebuilt using Scala 2.12 but Scala 2.4.5 is prebuilt with Scala 2.11 as mentioned at -

            This issue should go away if you use spark libraries compiled in 2.11



            Why I am getting ScalaTest-dispatcher NPE error with Intellij, maven and scala testing?
            Asked 2020-Oct-01 at 14:47

            I am getting this error when I try to run spark test in local :



            Answered 2020-Oct-01 at 14:47

            My problem come from a spark error about union 2 dataframe that i can't, but the message is not explict.

            If you have the same problem, you can try your test with a local spark session.

            remove DataFrameSuiteBase from your test class and instead make a local spark session:

            Before :



            How to fix "origin location must be absolute" error in sbt project (with Spark 2.4.5 and DeltaLake 0.6.1)?
            Asked 2020-Jun-23 at 10:20

            I am trying to setup a SBT project for Spark 2.4.5 with DeltaLake 0.6.1 . My build file is as follows.

            However seems this configuration cannot resolve some dependencies.



            Answered 2020-Jun-23 at 10:17

            I haven't managed to figure it out myself when and why it happens, but I did experience similar resolution-related errors earlier.

            Whenever I run into issues like yours I usually delete the affected directory (e.g. /Users/ashika.umagiliya/.m2/repository/org/antlr) and start over. It usually helps.

            I always make sure to use the latest and greatest sbt. You seem to be on macOS so use brew update early and often.

            I'd also recommend using the latest and greatest for the libraries, and more specifically, for Spark it'd be 2.4.6 (in the 2.4.x line) while Delta Lake should be 0.7.0.



            Inconsistency between local trained and Dataproc trained Spark ML model
            Asked 2020-May-28 at 20:02

            I am upgrading Spark from version 2.3.1 to 2.4.5. I am retraining a model with Spark 2.4.5 on Google Cloud Platform's Dataproc using Dataproc image 1.4.27-debian9. When I load the model produced by the Dataproc on my local machine using Spark 2.4.5 to validate the model. Unfortunately, I am getting the following exception:



            Answered 2020-May-28 at 20:02

            Spark in Dataproc back-ported a fix for SPARK-25959 that can cause this inconsistency between your local-trained and Dataproc-trained ML models.



            Spark: Add column with map logic without using UDF
            Asked 2020-May-17 at 07:41

            Basically, I want to apply my function countSimilarColumns on each row of dataframe and put the result in a new column.

            My code is as follows



            Answered 2020-May-16 at 14:59

            flattenData is of type DataFrame & applying map function on flattenData will get result of Dataset.

            You are passing result of => countSimilarColumns(row, referenceCustomerRow)) to withColumn but withColumn can only take the data of type org.apache.spark.sql.Column

            So if you want to add above result without UDF to a column you have to use collect function & then pass it to lit

            Please check below code.



            On forcefully deletion of a spark pod driver, the driver is not getting restarted
            Asked 2020-May-03 at 20:11

            I have a spark streaming job that I am trying to submit by a spark-k8-operator. I have kept the restart policy as Always. However, on the manual deletion of the driver the driver is not getting restarted. My yaml:



            Answered 2020-May-03 at 20:11

            There was an issue with the spark-K8 driver, now it has been fixed and I can see the manually deleted driver getting restarted. Basically code was not handling default values


            OR just have the following config in place so that default values are not required"



            NullPointerException when referencing DataFrame column names with $ method call
            Asked 2020-Apr-12 at 11:31

            Following is a simple word count Spark App using DataFrame and the corresponding unit tests using spark-testingbase. It works if I use the following



            Answered 2020-Apr-12 at 03:11

            You should call/import sqlContext.implicits to access $(dollar sign) in your code


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


            No vulnerabilities reported

            Install spark-test

            You can download it from GitHub, Maven.
            You can use spark-test 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 spark-test 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 For Gradle installation, please refer .


            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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