This is the promised cleanup. This structure gets rid of a lot of
intermediate structures and encodes through associated types how the
object stores and path types are related.
The enums are still necessary to avoid having generics leak all over
the place, but the object store variants and path variants should always
match because they'll always come from the object store trait
implementations that use the associated types.
* chore: Update arrow + tokio deps
* chore: Use bleeding edge azure
* chore: Update aws + other deps
* fix: fmt
* fix: Switch to in-house version of routerify
* fix: Upgrade to hyper 0.14
The hyper::error module is now private; hyper::Error is the public
re-export
* fix: Upgrade cloud storage to get tokio upgrade
* fix: Upgrade open_telemetry
* fix: Do not call `panic::set_hook` during another panic
Doing so leads to a double panic which aborts the process.
* fix: new h2 error who dis
Co-authored-by: Carol (Nichols || Goulding) <carol.nichols@integer32.com>
Co-authored-by: Jake Goulding <jake.goulding@integer32.com>
* feat: Chunk Migration APIs and query data in the read buffer via SQL
* fix: Make code more consistent
* fix: fmt / clippy
* chore: Apply suggestions from code review
Co-authored-by: Carol (Nichols || Goulding) <193874+carols10cents@users.noreply.github.com>
* refactor: Remove unecessary Result and make chunks() infallable
* chore: Apply more suggestions from code review
Co-authored-by: Edd Robinson <me@edd.io>
Co-authored-by: Carol (Nichols || Goulding) <193874+carols10cents@users.noreply.github.com>
Co-authored-by: Carol (Nichols || Goulding) <193874+carols10cents@users.noreply.github.com>
Co-authored-by: Edd Robinson <me@edd.io>
* refactor: consolidate line protocol schema creation into data_types, and port code to use it
refactor: Port mutable buffer to use SchemaBuilder
* fix: doctest
* refactor: remove unecessary clippyisms
* docs: Improve comments via suggestions from code review
Co-authored-by: Edd Robinson <me@edd.io>
* refactor: use more idomatic try_ naming and TryInto trait
* docs: Change from line protocol data model to InfluxDB data model
* refactor: rename LP --> Influx in code
* feat: add support for UInteger type
Co-authored-by: Edd Robinson <me@edd.io>
Adds serialization with compression and checksum for WAL buffer segments.
This required a weird structure where the flatbuffer bytes of ReplicatedWrite were kept as a raw payload. I did this because otherwise each of the replicated writes would have been rebuilt in the segment.
The other thing that isn't ideal is that deserializing a segment actually marshals it into a Rust struct as opposed to keeping the entire thing as raw flatbuffers. We could update this later to have a concept of an open segment (regular rust stuct) and closed segments that are just the flatbuffers.
Refactors the API method errors.
The user of the API client needs to be able to distinguish between various error
states when an API request fails. The most ergonomic way of exposing this
information is by returning an error enum that is specific to each API method
(or at least the important ones with well defined failure modes) - currently
only the `create_database()` method has significant error states, so this is
the only one with a specific error type in this impl.
This change defines a bunch of API error codes in the API client, adds them to
the IOx API error response body, and maps them in the API client. Due to error
wrapping the error code mapping in the IOx server is less exhaustive than I had
hoped however.
* feat: implement chunk listing and snapshotting in mutable buffer
* fix: update to use latest version of string interner and remove custom clone
* docs: fix comment
Initialises a new library crate and implements a basic IOx API client.
The API client supports:
- ping
- create database
Care has been taken to abstract away the underlying HTTP client used
(reqwest) and avoid leaking it into the public API (error types is a
common leak!) This makes updating the HTTP client and/or swapping it for
something else a backwards compatible change for end users of the crate.
Outstanding items:
- move shared API types into a sensible location
- discriminate between various IOx error responses
The former doesn't need doing until we publish the crate and will likely
be rather invasive / conlict prone so aiming to merge this PR and then
move things around in a follow-up.
The latter would allow us to expose error conditions to the user such
that they can take actions to remidy the situation / know if the request
can or should be retried / etc. Currently we expose a string error
message when requests fail, requiring string matching and/or passing the
string higher in the stack (and thus punting the problem to the caller).
It would be very nice to have typed errors, but a detail I have left for
later.
Replaces the hand-rolled config system with a StructOpt managed config struct.
I've got most of it ported across, but the interaction between all the logging
config bits is complex! I've left what is there and hooked in the value from
the config struct (which directly replaces the env var in usage, as it also
sources from the env).
Closes#528
This patch adds support for Microsfot Azure Blob storage. The
implementations requires an account, a key and container name. They can
be configured via the environment variables `AZURE_STORAGE_ACCOUNT`,
`AZURE_STORAGE_MASTER_KEY` and `AZURE_STORAGE_CONTAINER`.
This adds a new function list_with_delimiter to the object store. This commit contains just the implementation for S3, leaving the others to be completed in follow on commits.
This has a fixed delimiter to ensure a directory structure is created. This delimiter should be dependent on platform and which object store is used. For any of the cloud object stores or in memory, the delimiter should be /. For the future disk based implementation it should be dependendent on if you're running on Windows or Linux.
I didn't use Stream for the return type because I found it difficult to work with and I don't think it actually added anything useful. The return ListResult struct has the next token and I prefer that the caller explicitly makes calls that go over the network so they're more aware of what's going on, where a Stream abstracts that away so it's hidden behind the scenes. We can easilsy add a Stream based version on top of this existing API if we want.
* feat: Create configuration system, port IOx to use it
* docs: Apply suggestions from code review
Co-authored-by: Paul Dix <paul@influxdata.com>
* fix: fix test for setting values
Co-authored-by: Paul Dix <paul@influxdata.com>
This adds benchmarks to the data_types crate for ReplicatedWrite. This is the first in a series to test benchmarking Flatbuffers vs. JSON for the WAL Segment format.
* refactor: Update docs, remove unused field
* refactor: rename partition -> chunk
* feat: Introduce new partition, which is a holder for Chunks
* refactor: Remove use of wal from mutable database
* refactor: cleanups, remove last direct use of chunks
* fix: delete old benchmarks
* fix: clippy sacrifice
* docs: tidy up comments
* refactor: remove unused error types
* chore: remove commented out tests
This moves the HTTP API over to Routerify, which has the basic route parsing logic that will enable the API design for IOx.
I had a little trouble with the error handling in Routerify so I ended up creating a macro for constructing error responses in the HTTP API. I'm not sure what I think of this pattern so I'm interested in what others think. Another option would be to have two functions for each API endpoint. One which is x_handler with a Routerify function signature. Then another which is just x that has the Result<Response<Body>, ApplicationError> return type, which would make using the ? operator work in those functions. That would eliminate the need for the return_err macro.
I'm happy to refactor to that if people prefer it.
This commit swaps out the std library `HashMap` for the implementation
provided by the `hashbrown` crate. Not only does this allow us to use
the raw entry API, but it increases performance through the use of a
faster non-crytographically safe hashing function. We do not need an
expensive hash function for this code path.
Benchmark improvements are roughly 20-40%.
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_20_columns_2_rows_500000
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_20_columns_2_rows_500000: Warming up for 3.0000 s
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_20_columns_2_rows_500000: Collecting 100 samples in estimated 6.5961 s (400 iterations)
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_20_columns_2_rows_500000: Analyzing
segment_read_group_all_time_vary_cardinality/cardinality_20_columns_2_rows_500000
time: [16.502 ms 16.527 ms 16.558 ms]
thrpt: [1.2079 Kelem/s 1.2101 Kelem/s 1.2120 Kelem/s]
change:
time: [-40.808% -40.616% -40.428%] (p = 0.00 < 0.05)
thrpt: [+67.863% +68.394% +68.942%]
Performance has improved.
Found 8 outliers among 100 measurements (8.00%)
4 (4.00%) high mild
4 (4.00%) high severe
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_200_columns_2_rows_500000
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_200_columns_2_rows_500000: Warming up for 3.0000 s
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_200_columns_2_rows_500000: Collecting 100 samples in estimated 5.0698 s (300 iterations)
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_200_columns_2_rows_500000: Analyzing
segment_read_group_all_time_vary_cardinality/cardinality_200_columns_2_rows_500000
time: [16.531 ms 16.542 ms 16.555 ms]
thrpt: [12.081 Kelem/s 12.090 Kelem/s 12.099 Kelem/s]
change:
time: [-43.304% -43.047% -42.810%] (p = 0.00 < 0.05)
thrpt: [+74.856% +75.582% +76.378%]
Performance has improved.
Found 8 outliers among 100 measurements (8.00%)
5 (5.00%) high mild
3 (3.00%) high severe
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_2000_columns_2_rows_500000
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_2000_columns_2_rows_500000: Warming up for 3.0000 s
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_2000_columns_2_rows_500000: Collecting 100 samples in estimated 5.2590 s (300 iterations)
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_2000_columns_2_rows_500000: Analyzing
segment_read_group_all_time_vary_cardinality/cardinality_2000_columns_2_rows_500000
time: [17.497 ms 17.568 ms 17.648 ms]
thrpt: [113.33 Kelem/s 113.84 Kelem/s 114.30 Kelem/s]
change:
time: [-38.468% -38.188% -37.880%] (p = 0.00 < 0.05)
thrpt: [+60.978% +61.782% +62.518%]
Performance has improved.
Found 12 outliers among 100 measurements (12.00%)
12 (12.00%) high severe
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_20000_columns_3_rows_500000
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_20000_columns_3_rows_500000: Warming up for 3.0000 s
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_20000_columns_3_rows_500000: Collecting 100 samples in estimated 7.0471 s (300 iterations)
Benchmarking segment_read_group_all_time_vary_cardinality/cardinality_20000_columns_3_rows_500000: Analyzing
segment_read_group_all_time_vary_cardinality/cardinality_20000_columns_3_rows_500000
time: [23.305 ms 23.320 ms 23.336 ms]
thrpt: [857.05 Kelem/s 857.64 Kelem/s 858.20 Kelem/s]
change:
time: [-35.933% -35.778% -35.648%] (p = 0.00 < 0.05)
thrpt: [+55.396% +55.711% +56.087%]
Performance has improved.
Found 3 outliers among 100 measurements (3.00%)
3 (3.00%) high mild
Benchmarking segment_read_group_all_time_vary_columns/cardinality_20000_columns_2_rows_500000
Benchmarking segment_read_group_all_time_vary_columns/cardinality_20000_columns_2_rows_500000: Warming up for 3.0000 s
Benchmarking segment_read_group_all_time_vary_columns/cardinality_20000_columns_2_rows_500000: Collecting 100 samples in estimated 6.8058 s (300 iterations)
Benchmarking segment_read_group_all_time_vary_columns/cardinality_20000_columns_2_rows_500000: Analyzing
segment_read_group_all_time_vary_columns/cardinality_20000_columns_2_rows_500000
time: [22.475 ms 22.540 ms 22.622 ms]
thrpt: [884.10 Kelem/s 887.31 Kelem/s 889.87 Kelem/s]
change:
time: [-34.249% -34.051% -33.768%] (p = 0.00 < 0.05)
thrpt: [+50.984% +51.633% +52.089%]
Performance has improved.
Found 11 outliers among 100 measurements (11.00%)
2 (2.00%) high mild
9 (9.00%) high severe
Benchmarking segment_read_group_all_time_vary_columns/cardinality_20000_columns_3_rows_500000
Benchmarking segment_read_group_all_time_vary_columns/cardinality_20000_columns_3_rows_500000: Warming up for 3.0000 s
Benchmarking segment_read_group_all_time_vary_columns/cardinality_20000_columns_3_rows_500000: Collecting 100 samples in estimated 7.0631 s (300 iterations)
Benchmarking segment_read_group_all_time_vary_columns/cardinality_20000_columns_3_rows_500000: Analyzing
segment_read_group_all_time_vary_columns/cardinality_20000_columns_3_rows_500000
time: [23.683 ms 23.724 ms 23.779 ms]
thrpt: [841.08 Kelem/s 843.02 Kelem/s 844.49 Kelem/s]
change:
time: [-34.575% -34.419% -34.241%] (p = 0.00 < 0.05)
thrpt: [+52.070% +52.482% +52.847%]
Performance has improved.
Found 9 outliers among 100 measurements (9.00%)
6 (6.00%) high mild
3 (3.00%) high severe
Benchmarking segment_read_group_all_time_vary_columns/cardinality_20000_columns_4_rows_500000
Benchmarking segment_read_group_all_time_vary_columns/cardinality_20000_columns_4_rows_500000: Warming up for 3.0000 s
Benchmarking segment_read_group_all_time_vary_columns/cardinality_20000_columns_4_rows_500000: Collecting 100 samples in estimated 5.1007 s (200 iterations)
Benchmarking segment_read_group_all_time_vary_columns/cardinality_20000_columns_4_rows_500000: Analyzing
segment_read_group_all_time_vary_columns/cardinality_20000_columns_4_rows_500000
time: [25.379 ms 25.456 ms 25.545 ms]
thrpt: [782.93 Kelem/s 785.67 Kelem/s 788.06 Kelem/s]
change:
time: [-37.254% -36.988% -36.701%] (p = 0.00 < 0.05)
thrpt: [+57.981% +58.699% +59.373%]
Performance has improved.
Found 10 outliers among 100 measurements (10.00%)
2 (2.00%) high mild
8 (8.00%) high severe
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_250000
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_250000: Warming up for 3.0000 s
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_250000: Collecting 100 samples in estimated 5.7756 s (400 iterations)
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_250000: Analyzing
segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_250000
time: [14.404 ms 14.411 ms 14.419 ms]
thrpt: [1.3870 Melem/s 1.3878 Melem/s 1.3885 Melem/s]
change:
time: [-28.007% -27.893% -27.798%] (p = 0.00 < 0.05)
thrpt: [+38.500% +38.683% +38.903%]
Performance has improved.
Found 7 outliers among 100 measurements (7.00%)
3 (3.00%) high mild
4 (4.00%) high severe
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_500000
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_500000: Warming up for 3.0000 s
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_500000: Collecting 100 samples in estimated 6.9256 s (300 iterations)
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_500000: Analyzing
segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_500000
time: [23.191 ms 23.299 ms 23.419 ms]
thrpt: [854.02 Kelem/s 858.42 Kelem/s 862.40 Kelem/s]
change:
time: [-32.647% -32.302% -31.912%] (p = 0.00 < 0.05)
thrpt: [+46.868% +47.715% +48.471%]
Performance has improved.
Found 11 outliers among 100 measurements (11.00%)
11 (11.00%) high severe
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_750000
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_750000: Warming up for 3.0000 s
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_750000: Collecting 100 samples in estimated 6.1544 s (200 iterations)
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_750000: Analyzing
segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_750000
time: [30.813 ms 30.859 ms 30.916 ms]
thrpt: [646.92 Kelem/s 648.10 Kelem/s 649.07 Kelem/s]
change:
time: [-37.155% -36.779% -36.436%] (p = 0.00 < 0.05)
thrpt: [+57.322% +58.174% +59.121%]
Performance has improved.
Found 12 outliers among 100 measurements (12.00%)
5 (5.00%) high mild
7 (7.00%) high severe
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_1000000
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_1000000: Warming up for 3.0000 s
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_1000000: Collecting 100 samples in estimated 7.8548 s (200 iterations)
Benchmarking segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_1000000: Analyzing
segment_read_group_all_time_vary_rows/cardinality_20000_columns_2_rows_1000000
time: [39.303 ms 39.349 ms 39.405 ms]
thrpt: [507.55 Kelem/s 508.27 Kelem/s 508.86 Kelem/s]
change:
time: [-36.857% -36.699% -36.576%] (p = 0.00 < 0.05)
thrpt: [+57.669% +57.975% +58.371%]
Performance has improved.
Found 14 outliers among 100 measurements (14.00%)
8 (8.00%) high mild
6 (6.00%) high severe
This commit provides functionality on top of the `GroupKey` type (a
vector of materialised values), which allows them to be comparable by
implementing `Ord`.
Then, using the `permutation` crate, it is possible sort all rows in a
result set based on the group keys, which will be useful for testing.
kodiakhq[bot]
Raphael Taylor-Davies
Jake Goulding
Andrew Lamb
Carol (Nichols || Goulding)
Carol (Nichols || Goulding)
Andrew Lamb
Dom
Paul Dix
Edd Robinson
Karsten Jeschkies
Paul Dix