Speed up SQL NOT IN query MySQL I have a query as part of my process, that I execute hundreds of times in a loop.

Initially, Table A contains all records (20mil).  Table B contains 0 records.
Primary key in both tables ID
the I execute:

select * from table A where a.ID not in (select ID from table b) limit 10000
##magic stuff in python
insert everything to table B, once again, .


Initially, the query runs super fast, but after Nth loop (100th+), size of table B increases, to the point where I it takes a bit of time to perform the NOT IN operation.

Does anyone have recommendations on how I can speed up the query?
- So far, I've tweaked the default mysql bugger to be 1.5gbs (ids are pretty small INTs, so that should be enough).

Caveats:

1) One way to do this would be to remove * from table A after I've processed them.  However, I want to keep table A in tact.

... only method I could think of I adding another column to table A (which I'd index) called 'PROCESSED'... then update that column with a second query once the records have been processed/posted, but I was hoping there was an easier solution.  

Thank you all in advance.
If your goal is to look at every row in A and do something with it, there is a much more efficient way.  (It seems that B is merely there to see what you have already processed.)

The reason for it getting slower is that it has to do more work as it gets farther into A -- namely skipping over the rows it has processed.  A processed flag might suffer the same malady.

So...

Walk through A processing chunks as you go.  Then remember where you left off so that the next 10000 will be right there, no searching.  I discuss that in more detail with an eye to DELETEing, but it can be adapted for other purposes:  http://mysql.rjweb.org/doc.php/deletebig#deleting_in_chunks  With that, B is unnecessary.

Partitioning

If you are thinking about partitioning the data by months, I have to ask you "Why?".  Here are some answers:


For performance?  You won't get any.
For rapid deletion of "old" data?  This is a good use case, but be sure to use PARTITION BY RANGE(...) and include the year, too.  More:  http://mysql.rjweb.org/doc.php/partitionmaint