pubsub-to-bigquery | highly configurable Google Cloud Dataflow pipeline | GCP library

by bomboradata Java Version: Current License: Apache-2.0

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | pubsub-to-bigquery Summary

pubsub-to-bigquery is a Java library typically used in Cloud, GCP applications. pubsub-to-bigquery has build file available, it has a Permissive License and it has low support. However pubsub-to-bigquery has 1 bugs and it has 1 vulnerabilities. You can download it from GitHub.

A highly configurable Google Cloud Dataflow pipeline that writes data into Google Big Query table from Pub/Sub

Support

Quality

Security

License

Reuse

Support

pubsub-to-bigquery has a low active ecosystem.

It has 64 star(s) with 6 fork(s). There are 7 watchers for this library.

It had no major release in the last 6 months.

There are 0 open issues and 1 have been closed. On average issues are closed in 435 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pubsub-to-bigquery is current.

Quality

pubsub-to-bigquery has 1 bugs (0 blocker, 0 critical, 1 major, 0 minor) and 17 code smells.

Security

pubsub-to-bigquery has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

pubsub-to-bigquery code analysis shows 1 unresolved vulnerabilities (1 blocker, 0 critical, 0 major, 0 minor).

There are 0 security hotspots that need review.

License

pubsub-to-bigquery 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.

Reuse

pubsub-to-bigquery releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

It has 415 lines of code, 5 functions and 3 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed pubsub-to-bigquery and discovered the below as its top functions. This is intended to give you an instant insight into pubsub-to-bigquery implemented functionality, and help decide if they suit your requirements.

Entry point for testing
Parses a XML document from the provided parameters

Get all kandi verified functions for this library.

pubsub-to-bigquery Key Features

No Key Features are available at this moment for pubsub-to-bigquery.

pubsub-to-bigquery Examples and Code Snippets

No Code Snippets are available at this moment for pubsub-to-bigquery.

Community Discussions

Trending Discussions on pubsub-to-bigquery

Unable to drain/cancel Dataflow job. It keeps pending state

GCloud Dataflow recreate BigQuery table if it gets deleted during job run

QUESTION

Unable to drain/cancel Dataflow job. It keeps pending state

Asked 2021-Feb-10 at 20:19

Some jobs are remaining with pending pending state and I can't cancel them.

How do I cancel the job.

Web console shows like this.

"The graph is still being analyzed."
All logs are "No entries found matching current filter."
Job status: "Starting..." There isn't appered a cancel button yet.

There are no instances in the Compute Engline tab.

What I did is below. I created a streaming job. it was simple template job, Pubsub subscription to BigQuery. I set machineType as e2-micro because it was just a testing.

I also tried to drain and cancel by gcloud but it doesn't work.

...

ANSWER

Answered 2021-Feb-10 at 12:47

In GCP console Dataflow UI, if you have running Dataflow jobs, you will see the "STOP" button just like the below image.

Press the STOP button.

When you successfully stop your job, you will see the status like below. (I was too slow to stop the job with the first try, so I had to test it again. :) )

Source https://stackoverflow.com/questions/66116354

QUESTION

GCloud Dataflow recreate BigQuery table if it gets deleted during job run

Asked 2020-Mar-22 at 14:36

I have set up a GCloud Dataflow pipeline which consumes messages from a Pub/Sub subscription, converts them to table rows and writes those rows to a corresponding BigQuery table.

Table destination is decided based on the contents of the Pub/Sub message and will occasionally lead to the situation that a table does not exist yet and has to be created first. For this I use create disposition CREATE_IF_NEEDED, which works great.

However, I have noticed that if I manually delete a newly created table in BigQuery while the Dataflow job is still running, Dataflow will get stuck and will not recreate the table. Instead I get an error:

...

ANSWER

Answered 2020-Mar-22 at 14:36

This is not possible in the current BigqueryIO connector. From the github link of the connector present here you will observe that for StreamingWriteFn which is what your code, the table creation process is done in getOrCreateTable and this is called in finishBundle. There is a map of createdTables that is maintained and in finishBundle the table gets created if it not is already present, once it is present and stored in the hashmap it is not re-created as shown below:-

Source https://stackoverflow.com/questions/60786744

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

Vulnerabilities

No vulnerabilities reported

Install pubsub-to-bigquery

You can download it from GitHub.
You can use pubsub-to-bigquery 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 pubsub-to-bigquery 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 maven.apache.org. For Gradle installation, please refer gradle.org .

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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