qldb | QLDB driver for node | AWS library

You should use async await for this type of data-loading scenario. This means that the code will be suspended while waiting for the request to return, and the thread can go off dealing with user input.

Using ExecuteReader can be slightly more performant than using a DataAdapter.

You can also bulk-add the controls to the flow-panel using AddRange

Got an answer from a QLDB specialist so going to answer my own question: the operations should have been wrapped in a single transaction so my original assumption was actually true. They are going to update the code sample to reflect this.

You could use Saga Pattern to ensure the whole process completes or fails.

Here's a primer ... https://medium.com/@lfgcampos/saga-pattern-8394e29bbb85

• I'd add 'reserved funds' owned collection to the Ledger Account.
• A Ledger Account will have 'Actual' balance and 'Available Balance'.
• 'Available Balance' is 'Actual' balance less the value of 'reserved funds'

Using a Saga to manage the flow:

1. Try to reserve funds on the Account aggregate. The Ledger Account will check its available balance (actual minus total of reserved funds) and if sufficient, add another reserved funds to its collection. If reservation succeeds, the account aggregate will return a reservation unique id. If reservation fails, then the entry cannot be posted.

2. Try to complete the double entry bookkeeping. If it fails, send a 'release reservation' command to the Account aggregate quoting the reservation unique id, which will remove the reservation and we're back to where we started.

3. After double entry bookkeeping is complete, send a command to Account to 'complete' reservation with reservation unique id. The Account aggregate will then remove the reservation and adjust its actual balance.

In this way, you can manage a distributed transaction without the possibility of an account going overdrawn.

The AWS SDK will look in a set of predefined places to find some credentials to supply to the service when it connects. According to the Spring Boot documentation:

Spring Cloud for AWS can automatically detect this based on your environment or stack once you enable the Spring Boot property cloud.aws.region.auto.

You can also set the region in a static fashion for your application:

There are many ways to achieve what you are trying to do. But picking up from your example, you might want to convert your result person into JSON directly, or you might want to use a library to generate that JSON. If it possible to convert from IonValue (of which IonStruct is an instance) to POJOs and then you could convert those to JSON using Jackson.

To immediately answer your question, there are a couple of ways that you can achieve what you're trying to do, based on the ION data type of the timeStamp field.

1/ If the data type is of the timestamps type i.e

There would be a record of the original record and its deletion in the ledger, which would be available through the history() function, as you pointed out. So there's no way to hide the bad behavior. It's a matter of hoping nobody knows to look for it. Again, as you pointed out.

You have a couple of options here. First, QLDB rolled-out fine-grained access control last week (announcement here). This would let you, say, prohibit deletes on a given table. See the documentation.

Another thing you can do is look for deletions or other suspicious activity in real-time using streaming. You can associate your ledger with a Kinesis Data Stream. QLDB will push every committed transaction into the stream where you can react to it using a Lambda function.

If you don't need real-time detection, you can do something with QLDB's export feature. This feature dumps ledger blocks into S3 where you can extract and process data. The blocks contain not just your revision data but also the PartiQL statements used to create the transaction. You can setup an EventBridge scheduler to kick off a periodic export (say, of the day's transactions) and then churn through it to look for suspicious deletes, etc. This lab might be helpful for that.

I think the best approach is to manage it with permissions. Keep developers out of production or make them assume a temporary role to get limited access.

Since the journal is an immutable history of every transaction ever committed to the ledger, if you use the Outbox pattern with QLDB, your ledger will contain a permanent history of messages that passed through your Outbox table. This is great if you need an unfalsifiable audit history of the messages queued for sending and a record of them being sent ("deleted" from the table). However, if you don't need that, then you'll be paying storage for those messages for the life of the ledger and not getting much value from it.

The typical event-driven approach would be to use QLDB's streaming feature, which associates a Kinesis Data Stream to your ledger. Every time you commit a transaction, QLDB will publish the transaction to the Kinesis Data Stream. This enables you to drive events from transactions occurring in your ledger. With this approach, you commit your business data to the ledger without worrying about the Outbox table. The document should contain the information you would need in your messaging. Upon commit, QLDB pushes the document(s) from the transaction into Kinesis where you process it using a Lambda function that sends the message onward.

One thing to note is that QLDB offers an at-least-once guarantee of delivering data into Kinesis. This means that you'll need to identify and handle (or just tolerate) potential duplicate messaging. You should always be thinking about idempotence in distributed systems anyway, though.

If you don't want to pay for Kinesis and don't need a real-time approach, there are things you can do with scheduled QLDB exports into S3 and some batch processing of the export files, but I'd start with streaming. DM me if you want to hear more about the export approach.

See also:

• https://docs.aws.amazon.com/qldb/latest/developerguide/streams.html
• https://qldb-immersionday.workshop.aws/en/lab4.html

LIMIT isn't currently supported by Amazon QLDB. Here's a more detailed answer to your question Pagination in QLDB.