cloud-integration | Spark cloud integration : tests , s3 committer

by hortonworks-spark Scala Version: Current License: Apache-2.0

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

kandi X-RAY | cloud-integration Summary

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

The cloud-integration repository provides modules to improve Apache Spark's integration with cloud infrastructures.

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Support

cloud-integration has a low active ecosystem.

It has 20 star(s) with 6 fork(s). There are 5 watchers for this library.

It had no major release in the last 6 months.

cloud-integration has no issues reported. There are 4 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of cloud-integration is current.

Quality

cloud-integration has no bugs reported.

Security

cloud-integration has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

cloud-integration 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.

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cloud-integration 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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cloud-integration Key Features

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cloud-integration Examples and Code Snippets

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Community Discussions

Trending Discussions on cloud-integration

Writing to Google Cloud Storage with v2 algorithm safe?

Add `hadoop-cloud` to Spark's classpath

Unable to get S3A Directory Committers to write files in Spark 3.0.0

ACRCloud music recognition in Android service

Getting H2O working on Nimbix cloud servers

QUESTION

Writing to Google Cloud Storage with v2 algorithm safe?

Asked 2021-Apr-05 at 13:23

For object stores whose consistency model means that rename-based commits are safe use the FileOutputCommitter v2 algorithm for performance; v1 for safety.

Is it safe to use the v2 algorithm to write out to Google Cloud Storage?

What, exactly, does it mean for the algorithm to be "not safe"? What are the concrete set of criteria to use to decide if I am in a situation where v2 is not safe?

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ANSWER

Answered 2021-Apr-03 at 18:42

https://databricks.com/blog/2017/05/31/transactional-writes-cloud-storage.html

We see empirically that while v2 is faster, it also leaves behind partial results on job failures, breaking transactionality requirements. In practice, this means that with chained ETL jobs, a job failure — even if retried successfully — could duplicate some of the input data for downstream jobs. This requires careful management when using chained ETL jobs.

It's safe as long as you manage partial writes on failure. And to elaborate, they mean safe in regard to rename safety in the part you quote. Of Azure, AWS and GCP only AWS S3 is eventual consistent and unsafe to use with the V2 algorithm even when no job failures happen. But GCP (nor Azure or AWS) is not safe in regards to partial writes.

Source https://stackoverflow.com/questions/66933229

QUESTION

Add `hadoop-cloud` to Spark's classpath

Asked 2020-Dec-11 at 21:17

Since the recent announcement of S3 strong consistency on reads and writes, I would like to try new S3A committers such as the magic one.

According to the Spark documentation, we need to add the two class paths: BindingParquetOutputCommitter and PathOutputCommitProtocol adde in this commit.

The official documentation suggests using Spark built with hadoop3.2 profile. Is there any way to add the two classes without recompiling Spark? (I cannot use already built Spark for some technical reasons)

I am using Spark 3.0.1

I already checked this answer but unfortunately, the OP switched to open source S3A committers to provided one by EMR.

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ANSWER

Answered 2020-Dec-11 at 21:17

You need a version of spark built with the -Phadoop-cloud module. which adds the new classes into spark-hadoop-cloud.jar, and adds in the relevant dependencies, which for S3A are

Source https://stackoverflow.com/questions/65239138

QUESTION

Unable to get S3A Directory Committers to write files in Spark 3.0.0

Asked 2020-Jul-02 at 15:10

We are using Spark 3.0.0 and we are trying to write to S3a using the new S3A committers that Ryan Blue at Netflix wrote and were added in Spark by steveloughran.

We are using the build without Hadoop (spark-3.0.0-bin-without-hadoop) and provide our own Hadoop Jars (Hadoop 3.2.1).

The original issue I was facing was that we were getting a class not found exception for org.apache.spark.internal.io.cloud.PathOutputCommitProtocol

Full trace below:

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ANSWER

Answered 2020-Jul-02 at 15:10

This surfaces when you have > 1 machine in the spark cluster but you aren't using a shared filesystem to propagate the data about pending commits into the final dir.

make sure that fs.s3a.committer.staging.tmp.path points to something in HDFS, not paths local to the machines

Not using HDFS? well, you'd better make sure s3guard is on (for consistent s3 listings), then I'd switch to the magic committer which is pure S3 -no need for any cluster FS. Do not attempt to use it without S3Guard unless you like invalid answers

w.r.t why no spark-hadoop-cloud artifact? didn't get built in the release. The fact it adds the entire AWS SDK to the download is probably a factor. You can build it yourself though -it is probably safer to do that than mix spark artifacts

Source https://stackoverflow.com/questions/62685633

QUESTION

ACRCloud music recognition in Android service

Asked 2018-Sep-25 at 01:31

I followed the demo app in the ACRCloud Android sdk. All the code for music recognition was in the activity.

I did the same but in a service. So can we initialize the ACRCloudClient in the service?(ACRCloudClient extends from Activity).

How can we then do it in the service if we can't.

I have the implementation code in the service in another question. Here is the link See this question

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ANSWER

Answered 2018-Apr-09 at 11:47

SDK can work in a service, but because SDK needs recording, it may be interrupted during execution in the background.Can your implementation code work now? You can set "this.mConfig.context = null", and ignore that null exception.

Source https://stackoverflow.com/questions/49727056

QUESTION

Getting H2O working on Nimbix cloud servers

Asked 2017-Jul-11 at 03:35

I am trying to build a new application on Nimbix so I can use the latest H2O releases (the H2O community versions on the Nimbix servers are outdated).

I have tried building a new application using the instructions provided here: http://docs.h2o.ai/h2o/latest-stable/h2o-docs/cloud-integration/nimbix.html

And using the Docker Repository: opsh2oai/h2oai_nae and the Git Source URL: http://github.com/h2oai/h2o3-nae

System architecture is set to Intel x86.

I pull the application and logout and log back in.

I can start a Jupyter notebook. However, I cannot import H2O (No module named 'h2o')

Also, it is not clear what the differences between H2o3, H2o3 for POWER8, and H2oAI?

In addition, which version has the GPU-enabled algos (H2O with GPU-Enabled Machine Learning)?

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ANSWER

Answered 2017-Jul-11 at 03:35

That's the wrong image, the right one is: opsh2oai/h2o3_nae and the GitHub you have is correct.
H2o3 is h2o-3, and "H2o3 for POWER8" is for IBM; the H2OAI is not meant to be public and has been removed.
We have not enabled GPU on the Nimbix cloud to-date.

Source https://stackoverflow.com/questions/45024544

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

Vulnerabilities

No vulnerabilities reported

Install cloud-integration

You can download it from GitHub.

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