* refactor: do not run de-dup in ingester for querier requests
This removes the entire de-dup logic from the inegster for querier
requests. Furthermore, it even removes the entire datafusion execution
from the querier and just dumps the in-memory record batches as quickly
as possible. No filters are applied. Note that even prior to this PR,
we've never applied projections (tracked by #5624).
**Pros:**
- speed up query planning within the querier (since we need the ingester
response for state reconciling)
- lowered ingester CPU load
**Cons:**
- more querier<>ingester network traffic
Closes#5602.
* test: extend query test case
* fix: ingester tests
Co-authored-by: kodiakhq[bot] <49736102+kodiakhq[bot]@users.noreply.github.com>
This is what DataFusion uses by default and I don't see a reason why we
should use such small batch sizes.
The affect is probably only visible in certain filter-aggregate queries
that don't focus on a single series (because there we likely end up with
1 or 2 batches only, esp. after #5250) for coarse-grained filters, esp.
when the filter key is not the first sort key.
Co-authored-by: kodiakhq[bot] <49736102+kodiakhq[bot]@users.noreply.github.com>
* chore: Update datafusion pin
* fix: Update for api
* fix: Explicitly set coalsce batch size
* fix: Update batch size as well
* fix: update tests for new explain plan, and improved coercion
* refactor: remove New from a test scenario setup
* test: add explain for 2 different chunk stages
* test: expplain for several chunks from both parquet and ingester