Major Description
The current Camel ddbstream implementation seems to incorrectly apply the concept of ShardIteratorType to the list of shards forming a DynamoDB stream rather than each shard individually.
According to the AWS documentation:
ShardIteratorType determines how the shard iterator is used to start reading stream records from the shard.
For example, for a given shard, when ShardIteratorType equal to LATEST, the AWS SDK will read the most recent data in that particular shard. However, when ShardIteratorType equal to LATEST, Camel will additionally use ShardIteratorType to determine which shard it considers amongst all the available ones in the stream: https://github.com/apache/camel/blob/6119fdc379db343030bd25b191ab88bbec34d6b6/components/camel-aws/camel-aws2-ddb/src/main/java/org/apache/camel/component/aws2/ddbstream/ShardIteratorHandler.java#L132
If my understanding is correct, shards in DynamoDB are modelled as a tree, with the child leaf nodes being the shards that are still active, i.e. the ones where new stream data will appear. These child shards will have a StartingSequenceNumber, but no EndingSequenceNumber.
The most common case is to have a single shard, or a single branch of parent and child nodes:
Shard0 | Shard1
In the above case, new data will be added to Shard1, and the Camel implementation which looks only at the last shard when ShardIteratorType is equal to LATEST, will be correct.
However, the tree can also look like this (see related example in the attached JSON output from the AWS CLI, where the shard number matches the index in the JSON list):
Shard0
/ \
Shard1 Shard2
/ \ / \
Shard3 Shard4 Shard5 Shard6
In this case, Camel will only consider Shard6, even though new data may be added to any of Shard3, Shard4, Shard5 or Shard6. This leads to updates being missed.
As far as I can tell, DynamoDB will split into multiple shards depending on the number of table partitions, which will either grow for a table with huge amounts of data, or when an exiting table with provisioned capacity is migrated to on-demand provisioning.
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