sparkling-water | Sparkling Water provides H2O functionality inside Spark
kandi X-RAY | sparkling-water Summary
kandi X-RAY | sparkling-water Summary
Sparkling Water provides H2O functionality inside Spark cluster
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QUESTION
I am running Spark 2.4.4 using Yarn and interfacing using RSparkling and Sparklyr
As per these instructions I've
- Installed Sparklyr
- Called the library for Sparklyr
- Removed any prior installs of H2O
- Installed the latest version of H2O (rel-zorn)
- Installed rsparkling 3.36.0.3-1-2.4
- Called the library for rsparkling
- Specified my spark_config()
- Successfully made a connection to Spark using Yarn
- 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 13:08It 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.
QUESTION
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 20:27In 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:
- click Home icon
- click "Shared" > "Create" > "Library"
- click "Maven" (as "Library Source")
- click "Search packages" link next to "Coordinates" box
- click dropdown box and choose "Maven Central"
- enter
ai.h2o.sparkling-water-package
into the "Query" box - choose recent "Artifact Id" with "Release" that matches your
rsparkling
version, for meai.h2o:sparkling-water-package_2.12:3.32.0.5-1-3.0
- click "Select" under "Options"
- click "Create" to create the Library
- thankfully, this required no changes to my Databricks R Notebook when run as a Databricks job
QUESTION
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 04:22To 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
QUESTION
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 13:34Why 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.
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