simple-backup | A simple mysql database backup library for php | SQL Database library

by coderatio PHP Version: v1.0.4 License: MIT

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

kandi X-RAY | simple-backup Summary

simple-backup is a PHP library typically used in Database, SQL Database applications. simple-backup has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

A simple mysql database backup library for php.

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Quality

Security

License

Reuse

Support

simple-backup has a low active ecosystem.

It has 32 star(s) with 7 fork(s). There are no watchers for this library.

It had no major release in the last 12 months.

There are 2 open issues and 1 have been closed. On average issues are closed in 295 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of simple-backup is v1.0.4

Quality

simple-backup has 0 bugs and 0 code smells.

Security

simple-backup has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

simple-backup code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

simple-backup is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

simple-backup releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

It has 1788 lines of code, 156 functions and 7 files.

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

Top functions reviewed by kandi - BETA

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

Import SQL from file
List values for a table
Handles creating event
Initializes the mysql configuration .
Create a new mysql connection
Insert the dump header
Open a file
Creates a database type adapter
Writes string to file
Checks if a string is valid

Get all kandi verified functions for this library.

simple-backup Key Features

No Key Features are available at this moment for simple-backup.

simple-backup Examples and Code Snippets

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Community Discussions

Trending Discussions on simple-backup

Replaying data into Apache Beam pipeline over Google Cloud Pub/Sub without overloading other subscribers

Does the events in the same partition go to the same FlowFile using Kafka Consumer in NiFi

QUESTION

Replaying data into Apache Beam pipeline over Google Cloud Pub/Sub without overloading other subscribers

Asked 2019-Mar-08 at 22:47

What I'm doing: I'm building a system in which one Cloud Pub/Sub topic will be read by dozens of Apache Beam pipelines in streaming mode. Each time I deploy a new pipeline, it should first process several years of historic data (stored in BigQuery).

The problem: If I replay historic data into the topic whenever I deploy a new pipeline (as suggested here), it will also be delivered to every other pipeline currently reading the topic, which would be wasteful and very costly. I can't use Cloud Pub/Sub Seek (as suggested here) as it stores a maximum of 7 days history (more details here).

The question: What is the recommended pattern to replay historic data into new Apache Beam streaming pipelines with minimal overhead (and without causing event time/watermark issues)?

Current ideas: I can currently think of three approaches to solving the problem, however, none of them seem very elegant and I have not seen any of them mentioned in the documentation, common patterns (part 1 or part 2) or elsewhere. They are:

Ideally, I could use Flatten to merge the real-time ReadFromPubSub with a one-off BigQuerySource, however, I see three potential issues: a) I can't account for data that has already been published to Pub/Sub, but hasn't yet made it into BigQuery, b) I am not sure whether the BigQuerySource might inadvertently be rerun if the pipeline is restarted, and c) I am unsure whether BigQuerySource works in streaming mode (per the table here).
I create a separate replay topic for each pipeline and then use Flatten to merge the ReadFromPubSubs for the main topic and the pipeline-specific replay topic. After deployment of the pipeline, I replay historic data to the pipeline-specific replay topic.
I create dedicated topics for each pipeline and deploy a separate pipeline that reads the main topic and broadcasts messages to the pipeline-specific topics. Whenever a replay is needed, I can replay data into the pipeline-specific topic.

...

ANSWER

Answered 2019-Mar-08 at 22:47

Out of your three ideas:

The first one will not work because currently the Python SDK does not support unbounded reads from bounded sources (meaning that you can't add a ReadFromBigQuery to a streaming pipeline).
The third one sounds overly complicated, and maybe costly.

I believe your best bet at the moment is as you said, to replay your table into an extra PubSub topic that you Flatten with your main topic, as you rightly pointed out.

I will check if there's a better solution, but for now, option #2 should do the trick.

Also, I'd refer you to an interesting talk from Lyft on doing this for their architecture (in Flink).

Source https://stackoverflow.com/questions/55066449

QUESTION

Does the events in the same partition go to the same FlowFile using Kafka Consumer in NiFi

Asked 2019-Jan-18 at 16:08

The post sets the Max Poll Records to 1 to guarantee the events in one flow file come from the same partition. https://community.hortonworks.com/articles/223849/simple-backup-and-restore-of-kafka-messages-via-ni.html

Does that mean if using Message Demarcator, the events in the same FlowFile can be from different partitions?

from the source code I think the above thinking is true? https://github.com/apache/nifi/blob/ea9b0db2f620526c8dd0db595cf8b44c3ef835be/nifi-nar-bundles/nifi-kafka-bundle/nifi-kafka-0-9-processors/src/main/java/org/apache/nifi/processors/kafka/pubsub/ConsumerLease.java#L366

...

ANSWER

Answered 2019-Jan-18 at 16:08

When using a demarcator it creates a bundle per topic/partition, so you will get flow files where all messages are from the same topic partition:

https://github.com/apache/nifi/blob/ea9b0db2f620526c8dd0db595cf8b44c3ef835be/nifi-nar-bundles/nifi-kafka-bundle/nifi-kafka-0-9-processors/src/main/java/org/apache/nifi/processors/kafka/pubsub/ConsumerLease.java#L378

The reason that post set max pool records to 1 was explained in the post, it was because the key of the messages is only available when there is 1 message per flow file, and they needed the key in this case. In general, it is better to not do this and to have many messages per flow file.

Source https://stackoverflow.com/questions/54257496

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