sparkling-water | Sparkling Water provides H2O functionality inside Spark

 by   h2oai Scala Version: RELEASE-3.40.0.4-1 License: Apache-2.0

kandi X-RAY | sparkling-water Summary

kandi X-RAY | sparkling-water Summary

sparkling-water is a Scala library typically used in Big Data, Spark applications. sparkling-water has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. You can download it from GitHub.

Sparkling Water provides H2O functionality inside Spark cluster
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            kandi-support Support

              sparkling-water has a medium active ecosystem.
              It has 943 star(s) with 369 fork(s). There are 179 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 135 open issues and 2928 have been closed. There are 6 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of sparkling-water is RELEASE-3.40.0.4-1

            kandi-Quality Quality

              sparkling-water has 0 bugs and 0 code smells.

            kandi-Security Security

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

            kandi-License License

              sparkling-water 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

              sparkling-water releases are not available. You will need to build from source code and install.
              It has 38786 lines of code, 3211 functions and 776 files.
              It has medium code complexity. Code complexity directly impacts maintainability of the code.

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            sparkling-water Key Features

            No Key Features are available at this moment for sparkling-water.

            sparkling-water Examples and Code Snippets

            No Code Snippets are available at this moment for sparkling-water.

            Community Discussions

            QUESTION

            Error when creating H2O context using RSparkling
            Asked 2022-Mar-25 at 20:41

            I am running Spark 2.4.4 using Yarn and interfacing using RSparkling and Sparklyr

            As per these instructions I've

            1. Installed Sparklyr
            2. Called the library for Sparklyr
            3. Removed any prior installs of H2O
            4. Installed the latest version of H2O (rel-zorn)
            5. Installed rsparkling 3.36.0.3-1-2.4
            6. Called the library for rsparkling
            7. Specified my spark_config()
            8. Successfully made a connection to Spark using Yarn
            9. Ran h2oConf <- H2OConf()

            When I try to make a H2O context using the h2oConf above I get the following error:

            ...

            ANSWER

            Answered 2022-Mar-25 at 13:08

            It seems that your environment still contains old H2O R library. cacert is an valid parameter and it was introduced in H2O 3.26.0.6.

            Source https://stackoverflow.com/questions/71616995

            QUESTION

            Start H2O context on Databricks with rsparkling
            Asked 2021-Apr-22 at 20:27
            Problem

            I want to use H2O's Sparkling Water on multi-node clusters in Azure Databricks, interactively and in jobs through RStudio and R notebooks, respectively. I can start an H2O cluster and a Sparkling Water context on a rocker/verse:4.0.3 and a databricksruntime/rbase:latest (as well as databricksruntime/standard) Docker container on my local machine but currently not on a Databricks cluster. There seems to be a classic classpath problem.

            ...

            ANSWER

            Answered 2021-Apr-22 at 20:27

            In my case, I needed to install a "Library" to my Databricks workspace, cluster, or job. I could either upload it or just have Databricks fetch it from Maven coordinates.

            In Databricks Workspace:

            1. click Home icon
            2. click "Shared" > "Create" > "Library"
            3. click "Maven" (as "Library Source")
            4. click "Search packages" link next to "Coordinates" box
            5. click dropdown box and choose "Maven Central"
            6. enter ai.h2o.sparkling-water-package into the "Query" box
            7. choose recent "Artifact Id" with "Release" that matches your rsparkling version, for me ai.h2o:sparkling-water-package_2.12:3.32.0.5-1-3.0
            8. click "Select" under "Options"
            9. click "Create" to create the Library
              • thankfully, this required no changes to my Databricks R Notebook when run as a Databricks job

            Source https://stackoverflow.com/questions/67201421

            QUESTION

            Trying to install H2O on Databricks. How can I install a 3rd party package in Databricks?
            Asked 2020-Jul-22 at 04:22

            I'm playing around with Databricks now, and looking at a demo online. The demo requires H2O to be installed. In Databricks, I tried the following:

            ...

            ANSWER

            Answered 2020-Jul-22 at 04:22

            To make third-party or locally-built code available to notebooks and jobs running on your clusters, you can install a library. Libraries can be written in Python, Java, Scala, and R. You can upload Java, Scala, and Python libraries and point to external packages in PyPI, Maven, and CRAN repositories.

            Steps to install third party libraries:

            Method1: Using Maven

            Step1: Create Databricks Cluster.

            Step2: Select the cluster created.

            Step3: Select Libraries => Install New => Select Library Source = "Maven" => Coordinates => Search Packages => Select Maven Central => Search for the package required. Example: (ai.h20) => Select the version (sparkling-water-package_2.11:3.30.0.6-1-2.4) required => Install

            Method2: Using PYPI

            Step1: Create Databricks Cluster.

            Step2: Select the cluster created.

            Step3: Select Libraries => Install New => Select Library Source = "PyPI" => Coordinates => Enter Packages => h2o-pysparkling-2.4 => Install

            Method3: Using pip install

            Source https://stackoverflow.com/questions/63026551

            QUESTION

            H2OGridSearch H2OGBM pyspark: NullPointerException in extractH2OParameters
            Asked 2020-Feb-18 at 13:42

            I'm trying to run a grid search for Gradient Boosting Machine in pyspark with H2O Sparkling Water.

            Produced a reproducible example with the famous iris dataset.

            ...

            ANSWER

            Answered 2020-Feb-15 at 13:34

            Why not use a workaround and utilize H2O UI to create the grid? There's a checkbox to make your chosen parameter griddable, and you can supply the parameter values as a comma-separated list via the web form where you would normally put a single value.

            Source https://stackoverflow.com/questions/60094702

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

            Vulnerabilities

            No vulnerabilities reported

            Install sparkling-water

            You can download it from GitHub.

            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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          • HTTPS

            https://github.com/h2oai/sparkling-water.git

          • CLI

            gh repo clone h2oai/sparkling-water

          • sshUrl

            git@github.com:h2oai/sparkling-water.git

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