* feat: Make parquet_file.partition_id optional in the catalog
This will acquire a short lock on the table in postgres, per:
<https://stackoverflow.com/questions/52760971/will-making-column-nullable-lock-the-table-for-reads>
This allows us to persist data for new partitions and associate the
Parquet file catalog records with the partition records using only the
partition hash ID, rather than both that are used now.
* fix: Support transition partition ID in the catalog service
* fix: Use transition partition ID in import/export
This commit also removes support for the `--partition-id` flag of the
`influxdb_iox remote store get-table` command, which Andrew approved.
The `--partition-id` filter was getting the results of the catalog gRPC
service's query for Parquet files of a table and then keeping only the
files whose partition IDs matched. The gRPC query is no longer returning
the partition ID from the Parquet file table, and really, this command
should instead be using `GetParquetFilesByPartitionId` to only request
what's needed rather than filtering.
* feat: Support looking up Parquet files by either kind of Partition id
Regardless of which is actually stored on the Parquet file record.
That is, say there's a Partition in the catalog with:
Partition {
id: 3,
hash_id: abcdefg,
}
and a Parquet file that has:
ParquetFile {
partition_hash_id: abcdefg,
}
calling `list_by_partition_not_to_delete(PartitionId(3))` should still
return this Parquet file because it is associated with the partition
that has ID 3.
This is important for the compactor, which is currently only dealing in
PartitionIds, and I'd like to keep it that way for now to avoid having
to change Even More in this PR.
* fix: Use and set new partition ID fields everywhere they want to be
---------
Co-authored-by: Dom <dom@itsallbroken.com>
This interface was once specially implemented by the RUB. The only
actual implementation of it is within the querier that just forwards it
to a simple schema scan. Lift this semantic to `iox_query_influxrpc`
instead so all the chunks can use it.
If we ever want to optimize this again, we should use `QueryChunk::data`
instead (i.e. instead of implementing it within the chunk it should use
the data method and do something smart based on that).
First half of #8096.
This will hold the deterministic ID for partitions.
Until all existing partitions have this value, this is optional/nullable.
The row ID still exists and is used as the main foreign key in the
parquet_file and skipped_compaction tables.
The hash_id has a unique index so that we can look up records based on
it (if it's available).
If the parquet file record has a partition_hash_id value, use that to
generate the object storage path instead of the partition_id.
Nothing gets the partition ID out of the metadata. The parts of the code
interacting with object storage that need the ID to create the object
store path were using the partition ID from the metadata out of
convenience, but I changed those places to pass in the partition ID in a
separate argument instead.
This will make the transition to deterministic partition IDs a bit
smoother.
Co-authored-by: kodiakhq[bot] <49736102+kodiakhq[bot]@users.noreply.github.com>
* chore: Update DataFusion pin
* chore: Update cargo
* fix: update for API changes
* fix: Update plans
* chore: Update for new api
* fix: Update plans
* chore: Update for API changes more
---------
Co-authored-by: kodiakhq[bot] <49736102+kodiakhq[bot]@users.noreply.github.com>
This commit fixes loads of crates (47!) had unused dependencies, or
mis-configured dependencies (test deps as normal deps).
I added the "unused_crate_dependencies" to all crates to help prevent
this mess from growing again!
https://doc.rust-lang.org/beta/nightly-rustc/rustc_lint_defs/builtin/static.UNUSED_CRATE_DEPENDENCIES.html
This has the minor downside of false-positives when specifying
dev-dependencies for test/bench binaries - these are files in /test or
/benches (not normal tests). This commit includes a workaround,
importing them in lib.rs (gated by a feature flag). I think the
trade-off of better dependency management is worth it!
* chore: Update datafusion + arrow/parquet/arrow-flight to 36
* refactor: update optimize for new API
* refactor: update parquet for new API
* chore: Update more dependencies
* chore: Update to use the new buffer creation APIs
* chore: Run cargo hakari tasks
* fix: bad len
* fix: update for API change
---------
Co-authored-by: CircleCI[bot] <circleci@influxdata.com>
Co-authored-by: kodiakhq[bot] <49736102+kodiakhq[bot]@users.noreply.github.com>
* feat: Updating to new services for all-in-one
* fix: Use correct shard id for ingester2
* fix: clippy
* fix: use wal directory
* fix: end to end tests
* fix: Update tracing cases for new ingest reality
* fix: update metrics test
* fix: Use rpc mode
---------
Co-authored-by: Andrew Lamb <andrew@nerdnetworks.org>
Co-authored-by: Andrew Lamb <alamb@influxdata.com>
* feat: introduce a new way of max_sequence_number for ingester, compactor and querier
* chore: cleanup
* feat: new column max_l0_created_at to order files for deduplication
* chore: cleanup
* chore: debug info for chnaging cpu.parquet
* fix: update test parquet file
Co-authored-by: Marco Neumann <marco@crepererum.net>
* feat: introduce scratchpad store for compactor
Use an intermediate in-memory store (can be a disk later if we want) to
stage all inputs and outputs of the compaction. The reasons are:
- **fewer IO ops:** DataFusion's streaming IO requires slightly more
IO requests (at least 2 per file) due to the way it is optimized to
read as little as possible. It first reads the metadata and then
decides which content to fetch. In the compaction case this is (esp.
w/o delete predicates) EVERYTHING. So in contrast to the querier,
there is no advantage of this approach. In contrary this easily adds
100ms latency to every single input file.
- **less traffic:** For divide&conquer partitions (i.e. when we need to
run multiple compaction steps to deal with them) it is kinda pointless
to upload an intermediate result just to download it again. The
scratchpad avoids that.
- **higher throughput:** We want to limit the number of concurrent
DataFusion jobs because we don't wanna blow up the whole process by
having too much in-flight arrow data at the same time. However while
we perform the actual computation, we were waiting for object store
IO. This was limiting our throughput substantially.
- **shadow mode:** De-coupling the stores in this way makes it easier to
implement #6645.
Note that we assume here that the input parquet files are WAY SMALLER
than the uncompressed Arrow data during compaction itself.
Closes#6650.
* fix: panic on shutdown
* refactor: remove shadow scratchpad (for now)
* refactor: make scratchpad safe to use
Carol (Nichols || Goulding)
dependabot[bot]
Marco Neumann
Carol (Nichols || Goulding)
Andrew Lamb
Andrew Lamb
Dom Dwyer
kayagokalp
Raphael Taylor-Davies
Stuart Carnie
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