AWS Dynamodb扫描顺序？

Question

We have a setup where various worker nodes perform computations and update their relative states in a DynamoDB table. The table acts as a kind of history of activity of the worker nodes. A watchdog node needs to periodically scan through the table, and build an object representing the current state of the worker nodes and their jobs. As such, it's important for our application to be able to scan the table and retrieve data in chronological order (ie sorted by timestamp). The table will eventually be too large to scan into local memory for later ordering, so we cannot sort it after scanning.

Reading from the AWS documentation about the primary key:

DynamoDB uses the partition key value as input to an internal hash function. The output from the hash function determines the partition (physical storage internal to DynamoDB) in which the item will be stored. All items with the same partition key are stored together, in sorted order by sort key value .

Documentation on the scan function doesn't seem to mention anything about the order of the returned results. But can that last part in the quote above (the part I emphasized in bold) be interpreted to mean that the results of scans are ordered by the sort key? If I set all partition keys to be the same value, say "0", then use my timestamp as the sort key, can I be guaranteed that the scan operation will return data in chronological order?

Some note:

• All code is written in Python, and thus I'm using the boto3 module to perform scan operations.
• Our system architect is steadfast against the idea of updating any entries in the table to reflect their current state, or deleting items when the job is complete. We can only ever add to the table, and thus we need to scan through the whole thing each time to determine the worker states.
• I am using strong read consistency for scan operations.

Answer 1

Technically SCAN never guarantees order (although as an observation the lack of order guarantee seems to mean that the partition is randomly ordered, but the sort remains, well, sorted.)

What you've proposed will work however, but instead of scanning, you'll be doing a query on partition-key == 0 , which will then return all the items with the partition key of 0 , (up to limit and optional sorted forward/backwards) sorted by the sort key.

That said, this is really not the way that dynamo wants you to use it. For example, it guarantees your partition will run hot (because you've explicitly put everything on the same partition), and this operation will cost you the capacity of reading every item on the table.

I would recommend investigating patterns such as using a dynamodb stream processed by a lambda to build and maintain a materialised view of this "current state", rather than "polling" the table with this expensive scan and resulting poor key design.

Answer 2

You're better off using yyyy-mm-dd as the partition key, rather than all 0 . There's a limit of 10 GB of data per partition, which also means you can't have more than 10 GB of data per partition key value.

If you want to be able to retrieve data sorted by date, take the ISO 8601 time stamp format (roughly yyyy-mm-ddThh-mm-ss.sss ), split it somewhere reasonable for your data, and use the first part as the partition key and the second part as the sort key. (Another advantage of this approach is that you can use eventually consistent reads for most of the queries since it's pretty safe to assume that after a day (or an hour o something) that the data is completely replicated.)

If you can manage it, it would be even better to use Worker ID or Job ID as a partition key, and then you could use the full time stamp as the sort key.

As @thomasmichaelwallace mentioned, it would be best to use DynamoDB streams with Lambda to create a materialized view.

Now, that being said, if you're dealing with jobs being run on workers, then you should also consider whether you can achieve your goal by using a workflow service rather than a database. Workflows will maintain a job history and/or current state for you. AWS offers Step Functions and Simple Workflow .