Oracle GoldenGate 23ai: The Replicat Process
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Lois: Hello and welcome to another episode of the Oracle University Podcast. I’m Lois Houston, Director of Innovation Programs with Oracle University, and with me is Nikita Abraham, Team Lead: Editorial Services.
Nikita: Hi everyone! If you’ve been listening to us these last few weeks, you’ll know we’ve been discussing the fundamentals of GoldenGate 23ai. Today is going to be all about the Replicat process. Again, this is something we’ve discussed briefly in earlier episodes, but just to recap, the Replicat process applies changes from the source database to the target database. It's responsible for reading trail files and applying the changes to the target system.
Lois: That’s right, Niki. And we’ll be chatting with Nick Wagner, Senior Director of Product Management for Oracle GoldenGate. Hi Nick! Thanks for joining us again today. Let’s get straight into it. Can you give us an overview of the Replicat process?
Nick: One thing that's very important is the Replicat is extremely chatty with that target database. So it's going to be going in and trying to make lots of little transactions on that system. The Replicat process only issues single row DML.
So if you can imagine a source database that's generating hundreds of thousands of changes per second, we're going to have to have a Replicat process that can do 100,000 changes per second on that target site. That means that it's going to have to send a lot of little one record commands. And so we've got a lot of ways to optimize that.
But in all situations you're really going to want very, very low ping time between that Replicat process and that target database. This often means that if you're going to be running GoldenGate in a cloud, you're going to want the Cloud GoldenGate environment to be running in that target data center, wherever that target database is.
Lois: What are the key characteristics of the process, Nick?
Nick: Replicat process is going to read the changes from the trail file and then apply them to the target system, just like any database user would. It's not doing anything special where it's going under the covers and trying to apply directly to the database blocks. It's just applying regular standard insert, update, delete, and DDL statements to that target database.
A single trail file does support high volume of data replication activity depending on the type of Replicat. Replicats do preserve the boundary of their transactions. So in the situations, by default, a transaction that's on the source, let's say five inserts followed by a commit will remain five inserts followed by a commit on the target site.
There are some operations and changes that do affect this, but they're not turned on by default. There are things like group transactions that allows you to group multiple transactions into a single commit. This one could actually improve performance in some cases. We also have batch SQL that can change the boundaries of a transaction as well.
And then in a Parallel Replicat, you actually have the ability to split a large transaction into multiple chunks and apply those chunks in Parallel. So again, by default, it's going to preserve the boundaries, but there are ways to change that. And then the Replicats use a checkpoint table to help with recovery and to know where they're applying data and what they've done.
The other thing in here is, like an Extract process can write to multiple trails and write subsets of data to each one, a Replicat can only process a single set of trail files at once. So it's going to be attached to a specific trail file like trail file AB, and will only be able to read changes from trail file AB. If I have multiple trails that need to be applied into a target system, then I have to set up multiple Replicats to handle that.
Nikita: So, what are the different Replicat types, Nick?
Nick: We have three types in the product today. We have Classic Replicat, which should really only be used for testing purposes or in environments that don't support any of the other specialized Replicats.
We have Coordinated Replicat, which is a high speed apply mechanism to apply data into a target system. It does have some parallelism in it, but it's user defined parallelism. And then we have our flagship and that's Parallel Replicat. And this is the most performant lowest latency Replicat that we have.
Lois: Ok. Let’s dive a little deeper into each of them, starting with the Classic Replicat. How does it work?
Nick: It's pretty straightforward. You're going to have a process that reads the trail files, and then in a single threaded fashion it's going to take the trail file logical change record, convert it to an insert, update, or delete, and then apply it into that target database.
Each transaction that it does is preceded by a change to the checkpoint table. So when the transaction that the Replicat is currently doing is committed, that checkpoint table update also gets committed. That way when the Replicat restarts, it knows exactly what transaction it left off and how it last applied the record.
And all the Replicats work the same way with regards to checkpoint tables. They each have their own little method of ensuring that the transaction they're applying is also reflected within the checkpoint table so that when it restarts, it knows exactly where it happened. That way, if a Replicat dies in the middle of a transaction, it can be restarted without any duplicate data or without missing data.
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Nikita: Welcome back! Moving on, what about Coordinated Replicat?
Nick: The Coordinated Replicat is going to read from a set of trail files. It's going to have multiple threads that do this.
So you have your base thread, your coordinated thread that's going to be thread 1. It's going to process the data and apply it into that target database. You then have thread 2, 4, 5, 6, and so on.
When you set up your Replicat parameter file for a Coordinated Replicat, the map commands that maps from one table on the source to a table on the target has an additional option. So you'll have an option called a range or thread range. With the range and thread range option, you can actually tell which table to go into which thread.
Lois: Can you give us an example of this?
Nick: So I could say map Scott.M into thread 1 and I want Scott.Dept into thread 2. Well, this is fantastic until you realize that Scott.M and Scott.Dept have a foreign key between them or a child dependencies, parent-child relationships. What that means is that now I'm going to have to disable that foreign key on the target site, because there's no way for GoldenGate to coordinate the changes in one thread to another thread.
And so you really have to be careful on how you pair your tables together. If you don't have any referential integrity on that target database, then you can use parallel coordinated Replicat to really high degrees of parallelism, and you get some very good performance out of it. Let's say that you have a table that's really got too much data for even a single thread to process, that's where the thread range comes in.
And thread range command will use something like the table's primary key to split transactions on that table across multiple threads. So I can say, hey, take my table Scott.M and I want to spread transactions across threads 10, 11, 12, 13, and 14 and then spread them evenly based on the primary key. And Coordinated Replicat will do that. So you can get some very high performance numbers out of it and you can really fine tune the tables, especially if you know the amount of data coming into each one.
While this does work great, we observed that a lot of custome
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