feat(bigquery): implement appends/changes event based cdc modes - #4707
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Capture T (BigQuery's own CURRENT_TIMESTAMP(), not local wall-clock) once per
ExportTxSnapshot call and append FOR SYSTEM_TIME AS OF TIMESTAMP('<T> UTC') to
every table's EXPORT DATA statement, so all tables in a snapshot read a
consistent point in time.
Persist T as the initial CDC checkpoint via SetLastOffset, but from
ExportTxSnapshot itself rather than SetupReplication as the plan originally
sketched: SnapshotFlowWorkflow only calls ExportTxSnapshot when
InitialSnapshotOnly is true, and only calls SetupReplication when it's false
(cloneTablesWithSlot, or the no-snapshot CDC-only branch) - the two are
mutually exclusive per run, so T is never in scope inside SetupReplication.
Gating the write on !InitialSnapshotOnly here is therefore a forward-looking
no-op until a later chunk changes how BigQuery mirrors that continue into CDC
get their initial load wired up; documented in code at the capture site.
Refactored the SQL-building half of bigQueryExportQueryStatement into a pure
buildBigQueryExportSQL taking an already-resolved schema, so it's unit
testable without a live BigQuery client (mirrors the existing
bigQuerySchemaToQRecordSchema/datasetTable test patterns in this package).
…t code ExportTxSnapshot only ever runs on SnapshotFlowWorkflow's pure snapshot-only branch (InitialSnapshotOnly && DoInitialSnapshot) - the continue-to-CDC and CDC-only branches call SetupReplication instead and never touch ExportTxSnapshot. So the checkpoint-persist code added there, gated on !InitialSnapshotOnly, could never actually run; removed. SetupReplication now does what MySQL's does: capture a starting position (BigQuery's current timestamp T, no replication slot to open) and persist it as the initial CDC checkpoint. Unlike MySQL, BigQuery's initial load reads pre-exported Parquet from GCS rather than querying the live table, so when the mirror wants an initial load (req.DoInitialSnapshot), this also runs that export as of T - the per-table export-job loop is factored out of ExportTxSnapshot into a shared exportTablesAsOf helper so both callers use it. Returns a zero-value SetupReplicationResult (no slot/snapshot name), same as MySQL: cloneTablesWithSlot falls back to the mirror's configured SnapshotStagingPath when no override is given, which is exactly where this export writes.
…bject_pull_test.go
Newline/tab padding made the query harder to read; collapse to single-line format string.
Introduces a connector-specific mirror-config extension point on FlowConnectionConfigs/FlowConnectionConfigsCore, mirroring how Peer already does this for peer-level config. BigqueryCdcConfig (with a cdc_mode of APPENDS or CHANGES) is the first variant. No converter work is needed: flow/proto_conversions copies between the two messages by field number, so a oneof - whose wrapper types are scoped per parent message - is carried over without special-casing. No behavior change yet - BigqueryCdcConfig is not read anywhere. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
start_peer_flow_job builds FlowConnectionConfigs as a fully exhaustive struct literal (no ..Default::default()), so it needs every field set explicitly. The new source_connector_config oneof broke this build; nexus doesn't set any connector-specific mirror config today, so None is correct here.
Copying by field number handles the oneof without special-casing, but the wrapper types are scoped per parent message, so assert the variant is rebuilt against the destination's own type in both directions - and that an unset oneof stays unset rather than spuriously populating a variant. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
…ecting Snapshot-only mirrors skip these checks (mirrors MySQL's ValidateMirrorSource pattern). CHANGES mode needs a real PK constraint plus enable_change_history on the source table; APPENDS mode needs an explicit MergeTree destination engine when there's no PK, since ORDER BY tuple() on a keyless ReplacingMergeTree collapses the table on writes.
…GE_TREE CH_ENGINE_REPLICATED_REPLACING_MERGE_TREE is the same collapsing dedup engine as the plain variant, just wrapped for replication (see how normalize.go's engine switch groups the two under one case) - a keyless table hits the same ORDER BY tuple() collapse either way, so the APPENDS-mode keyless-engine check needs to catch both.
Gives BigQueryConnector real CDCPullConnectorCore bodies (SetupReplConn, UpdateReplStateLastOffset, PullFlowCleanup, EnsurePullability) and a real PullRecords: self-paced polling of APPENDS() per mapped table over (checkpoint, upper], converting rows to InsertRecords via a new BigQuery value -> QValue converter, advancing the checkpoint text once the window closes. No delete/insert pairing yet -- that's CHANGES mode, next chunk.
CHANGES() reports an UPDATE as a delete+insert pair sharing the same PK and _CHANGE_TIMESTAMP, so PullRecords needs to pair those back into one UpdateRecord instead of emitting two records -- otherwise every update on a CHANGES-mode mirror would be replicated as a delete followed by an unrelated insert. Reads cdc_mode once per PullRecords call (it's a per-mirror setting) to pick APPENDS or CHANGES per the "Decisions locked in" plan.
- cleanup comments
…CHANGES bq functions
…st does not exist" error
Rewrites the now-stale Test_BigQuery_Source_CDC_Not_Supported, which asserted CDC gets rejected - chunk 3 replaced that with mode-specific validation. Adds e2e coverage for snapshot->CDC handoff, APPENDS insert-only polling, CHANGES insert/update/delete pairing, and pause/resume from the persisted checkpoint; none of this has been run against a live BigQuery instance yet.
- cleanup comments
bigquery.go holds the shared BigQueryConnector struct used by both source and destination code, so source-only changes there were wrongly picked up by the deprecated-connector labeler.
| return nil, err | ||
| } | ||
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| lastCheckpoint := recordBatchPull.GetLastCheckpoint() |
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we also periodically persist/advance on an idle stream for other connectors, but logic is implemented inside PullRecord since empty batch stays open until at least one record is received, so for consistency this could be moved to inside PullRecord.
| c.logger.Info("[bigquery] PullRecords polled window", | ||
| slog.Time("start", checkpoint), slog.Time("end", upper), | ||
| slog.Int("records", recordCount), slog.Int64("bytes", bytesProcessed)) |
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Nit: please add channelLen (to have telemetry for bottlenecks) and log end-start as elapsedMinutes float. slog.Time logs nanoseconds so it's less intuitive to skim when reading logs
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Haven't looked at the further PRs yet, but would be cool to also report records/bytes/channelLen in ongoing manner like in other connectors. This helps investigate tickets about a single batch taking long and OOMs
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oh yeah, I'll make sure we have all necessary logs in the follow-up PR
this PullRecords function is removed anyways in the follow-up in favor of PullTableRecords for isolated tables CDC
| // droppedExcludeColumns remembers, per source table, excluded columns that | ||
| // BigQuery has reported as no longer existing, so later polls stop asking BigQuery | ||
| // to EXCEPT them. | ||
| droppedExcludeColumns map[string]map[string]struct{} |
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Keep in mind the columns can come back too, so client-side filtering would be needed as well.
Also, maybe more of a product note: excluding columns in a way that we don't even see the data was an often requested feature in other source types, so EXCEPT here works great, but seems if we advertise it we'd need to caveat that it only works as long as the column is already present at the first batch and doesn't disappear-reappear. If it becomes an important first-party scenario, maybe could have some option to always query the known columns and not support column adds. Couldn't think of a way to have SELECT * EXCEPT fully work here, as even if we always do the elimination loop, an excluded column could get re-added in between retries and we'd receive the bytes.
| bigquery.TimestampFieldType: {types.QValueKindTimestamp, types.QValueKindArrayTimestamp}, | ||
| bigquery.DateTimeFieldType: {types.QValueKindTimestamp, types.QValueKindArrayTimestamp}, | ||
| bigquery.DateFieldType: {types.QValueKindDate, types.QValueKindArrayDate}, | ||
| bigquery.TimeFieldType: {types.QValueKindTime, types.QValueKindArrayString}, |
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Seems to be a miss that we don't have an QValueKindArrayTime. Mind adding it for BQ and creating a ticket for other connectors?
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- created a ticket for other connectors
| if fieldSchema.Type == bigquery.RecordFieldType { | ||
| // Preserve field names and values as JSON text in STRING or ARRAY<STRING> values. |
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Did we clear it with Product that JSON strings are desired here? BQ records are typed, CH has Nested, so seems like our internal bottleneck
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Tuple would be the best typed one, you're right
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changed to native JSON for Struct and ArrayString for repeated Struct (since we don't support Array(JSON) yet in peerdb)
| return fmt.Sprintf("[%s, %s)", bigQueryRangeBoundString(value.Start), bigQueryRangeBoundString(value.End)) | ||
| } | ||
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| func bigQueryRangeBoundString(value bigquery.Value) string { |
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Please add a subissue to DBI-295 or augment DBI-296 so we pretty it up at the same time
| TargetForSetting: protos.DynconfTarget_BIGQUERY, | ||
| }, | ||
| { | ||
| Name: "PEERDB_BIGQUERY_CDC_SAFETY_LAG_SECONDS", |
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Seems there was a 10 min restriction for CHANGES that got removed with GA: https://www.linkedin.com/feed/update/urn:li:activity:7488597379827445760/
For appends though, the outcome of underestimating this would be silently missing rows, right? Would it make sense to make it user-configurable somewhere in advanced settings? Also wonder if there's any telemetry we could insert to track this, even at a higher cost during private preview
Edit: reading further, seems CHANGES also doesn't document any guarantees wrt end_timestamp coverage, just that you can pass null and not get an error
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ah, didn't see the new review from @ilidemi coming in, just approving what I have reviewed so far. Please make sure to address the rest. |
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@ilidemi regarding this |
🔄 Flaky Test DetectedAnalysis: Flaky infrastructure failure: the pure-unit test TestRunPipeline_FilterStripsLines failed because its ✅ Automatically retrying the workflow |
- align qrep qField conversion with cdc path
❌ Test FailureAnalysis: Not flaky: all three matrix legs fail identically because PR #4707 changes the BigQuery TIMESTAMP mapping from QValueKindTimestamp to QValueKindTimestampTZ without updating the trips1kExpectedQValueColumns expectations in flow/e2e/bigquery_source_test.go. |
What
This PR makes BigQuery a valid source connector.
Mainly it implements PullRecords method and BigQuery CDC mirror validation. (check if ordering key is set for cdc mirrors, etc)
It supports two change capture modes:
The new replication mode setting was added to BigQuery mirrors:
and the new BQ specific setting was added to the table mapping struct (only relevant for
BIGQUERY_REPLICATION_MODE_EVENTSreplication mode):Important files for review
What is not included in this PR
Resolves: DBI-1038