Real time Change Data Capture in Talend - talend

I am trying to setup Real time change data capture between two different MySQL databases using Talend Studio. I was able to successfully create a job that uses Publish/Subscribe model that picks up only the changed data from source and populates in the target database.
I could not find the documentation to setup CDC in real time i.e. as soon as a new row is inserted in the source database it will be picked up by the job and populated in target database. The Talend job will be running continuously to look for possible changes in the source.
My question: is scheduling the Talend job using some scheduler for desired interval the only option in this case?
Thanks in advance.

You could also use triggers for Create, Update, Delete on the database and use those triggers to start a process pushing the data somewhere or starting a process.

Related

Cloud SQL: export data to CSV periodically avoiding duplicates

I want to export the data from Cloud SQL (postgres) to a CSV file periodically (once a day for example) and each time the DB rows are exported it must not be exported in the next export task.
I'm currently using a POST request to perform the export task using cloud scheduler. The problem here (or at least until I know) is that it won't be able to export and delete (or update the rows to mark them as exported) in a single http export request.
Is there any possibility to delete (or update) the rows which have been exported automatically with any Cloud SQL parameter in the http export request?
If not, I assume it should be done it a cloud function triggered by a pub/sub (using scheduler to send data once a day to pub/sub) but, is there any optimal way to take all the ID of the rows retrieved from the select statment (which will be use in the export) to delete (or update) them later?
You can export and delete (or update) at the same time using RETURNING.
\copy (DELETE FROM pgbench_accounts WHERE aid<1000 RETURNING *) to foo.txt
The problem would be in the face of crashes. How can you know that foo.txt has been writing and flushed to disk, before the DELETE is allowed to commit? Or the reverse, foo.txt is partially (or fully) written, but a crash prevents DELETE from committing.
Can't you make the system idempotent, so that exporting the same row more than once doesn't create problems?
You could use a set up to achieve what you are looking for: 
1.Create a Cloud Function to extract the information from the database that subscribes to a Pub/Sub topic.
2.Create a Pub/Sub topic to trigger that function.
3.Create a Cloud Scheduler job that invokes the Pub/Sub trigger.
4.Run the Cloud Scheduler job.
5.Then create a trigger which activate another Cloud Function to delete all the data require from the database once the csv has been created.
Here I leave you some documents which could help you if you decide to follow this path.
Using Pub/Sub to trigger a Cloud Function:https://cloud.google.com/scheduler/docs/tut-pub-sub
Connecting to Cloud SQL from Cloud Functions:https://cloud.google.com/sql/docs/mysql/connect-functionsCloud
Storage Tutorial:https://cloud.google.com/functions/docs/tutorials/storage
Another method aside from #jjanes would be to partition your database by date. This would allow you to create an index on the date, making exporting or deleting a days entries very easy. With this implementation, you could also create a Cron Job that deletes all tables older then X days ago.
The documentation provided will walk you through setting up a Ranged partition
The table is partitioned into “ranges” defined by a key column or set of columns, with no overlap between the ranges of values assigned to different partitions. For example, one might partition by date ranges, or by ranges of identifiers for particular business objects.
Thank you for all your answers. There are multiples ways of doing this, so I'm goint to explain how I did it.
In the database I have included a column which contains the date when the data was inserted.
I used a cloud scheduler with the following body:
{"exportContext":{"fileType": "CSV", "csvExportOptions" :{"selectQuery" : "select \"column1\", \"column2\",... , \"column n\" from public.\"tablename\" where \"Insertion_Date\" = CURRENT_DATE - 1" },"uri": "gs://bucket/filename.csv","databases": ["postgres"]}}
This scheduler will be triggered once a day and it will export only the data of the previous day
Also, I have to noticed that in the query I used in cloud scheduler you can choose which columns you want to export, doing this you can avoid to export the column which include the Insertion_Date and use this column only an auxiliary.
Finally, the cloud scheduler will create automatically the csv file in a bucket

How to trigger a Google Cloud Composer DAG based on a latest record in the control table

I have a DAG thet loads the data into no of raw tables .There is a control table that stores the list of tables and when they are last updated by the DAG .This is all managed by different ta=eam. I am trying to create a DAG to run a query on one of the raw table and load it into persistant table. I would like to run the DAG as soon as i see the latest time stamp than what i already processed in my control table.
I am new to the Cloud Composer, can you please let me know how i can accomplish it?
Thanks

IBM DB2 and IBM IMS Change Data Capture Capabilities

I'd like to understand if the CDC enabled IBM IMS segments and IBM DB2 table sources would be able to provide both the before and after snapshot change values (like the Oracle .OLD and .NEW values in trigger) so that both could be used for further processing.
Note:
We are supposed to retrieve these values through Informatica PowerExchange and process and push to targets.
As of now, we need to know would we be able to retrieve both before snapshot and after snapshot values from IBM DB2 and IBM IMS (.OLD and .NEW as in Oracle triggers - not an exact similar example, but mentioned just as an example to understand)
Any help is much appreciated, Thanks.
I don't believe CDC captures before data in its change messages that it compiles from the DBMS log data. It's main purpose is to issue the minimum number of commands needed to replicate the data from one database to another. You'll want to take a snapshot of your replica database prior to processing the change messages if you want to preserve the state of data such that you can query it.
Alternatively for Db2, it's probably easier to work with the temporal tables feature added in Db2 10 as that allows you to define what changes should drive a snapshot. You can then access the temporal data using a temporal SQL query.
SELECT … FROM…period specification
Example trigger with old and new referencing...
CREATE TRIGGER danny117
NO CASCADE BEFORE Update ON mylib.myfile
REFERENCING NEW AS N old as O
FOR EACH ROW
-- don't let the claim change and force upper case
--just do something automatically on update blah...
BEGIN ATOMIC
SET N.claim = ucase(O.claim);
END
w.r.t PowerExchange 9.1.0 & 9.6:
Before snapshot data can't be processed via the powerexchange for DB2 database. Recently I worked on a migration project and I thought like the Oracle CDC which uses SCN numbers there should be something for db2 to start the logger from any desired point. But to my surprise Inforamtica global support confirmed that before snapshot data can't be captured by PowerExchange.
They talk about materialize and de-materialize targets which was out of my knowledge at that time, later I found out they meant to export and import of history data.
Even if you have table with CDC enanbled, you can't capture the data before snapshot from PWX.
DB2 reads capture data from the DB2-logs which has a marking for the operation like U/I/D that's enough for PowerExchange to progress.

Talend open studio run only created or modified records among 15k

I have a job in talend open studio which is working fine, it conects a tMSSqlinput to a tMap then tMysqlOutput, very straight forward. My problem is that i need this job running on daily basis, but only run when a new record is created or modified...any help is highly aprecciated!
It seems that you are searching for a Change Data Capture Tool for Talend.
Unfortunately it is only available on the licenced product.
To implement your need, you do have several ways. I want to show the most popular ones.
CDC from Talend
As Corentin said correctly, you could choose to use CDC (Change Data Capture) from Talend if you use the subscription version.
CDC of MSSQL
Alternatively you can check if you can activate or use CDC in your MSSQL server. This depends on your license. If it is possible, you can use the function to identify new elements and proceed them.
Triggers
Also you can create triggers on your database (if you have access to it). For example, creating a trigger for the cases INSERT, UPDATE, DELETE would help you getting the deltas. Then you could store those records separately or their IDs.
Software driven / API
If your database is connected to a software and you have developers around, you could ask for a service which identifies records on insert / update / delete and shows them to you. This could be done e.g. in a REST interface.
Delta via ID
If the primary key is an ID and it is set to autoincrement, you could also check your MySQL table for the biggest number and only SELECT those from the source which have a bigger ID than you have already got. This depends of course from the database layout.

Set up delta load in azure data factory

I have an SQL database on prem that I want to get data from. In the database there is a column called last_update that has information about when a row was last updated. The first time I run my pipeline I want it to copy everything from the database on prem to an azure database. The next time I want copy only the rows that have been updated since the last run. I therefore want to copy everything where last_update is higher than the time of the last run. Is there a way of using information about the time of the last run in a pipeline? Is there any other good way of creating what i want?
I think you can do this by developing custom copy activity. You can add your own transformation/processing logic and use the activity in a pipeline.