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perf(spanner): optimize query result decoding and type resolution - #18330
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Improve query result decoding performance in StreamedResultSet and simplify
type decoder resolution in _helpers.
* Optimize row construction in StreamedResultSet._merge_values:
- Process complete rows in batch using direct column indexing rather than
iterating cell-by-cell with repeated append() calls and boundary checks.
- For lazy decoding, slice raw values directly into rows.
- Add an explicit guard for width == 0 to prevent unbounded buffer growth
on empty schemas.
- Separate partial row boundary handling from complete row decoding by
extracting _append_to_current_row, _decode_eager_rows, and
_decode_lazy_rows, removing duplicated cell-appending logic.
* Optimize type resolution in _helpers:
- Replace the if/elif cascade in _get_type_decoder with an integer-keyed
_SCALAR_DECODERS lookup table.
- Pre-allocate static decoder callables at module scope to avoid lambda
recreation when resolving column metadata.
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This pull request refactors and optimizes row decoding and value merging in both synchronous and asynchronous streamed result sets, introducing batch-decoding helpers and mapping scalar type codes to a pre-defined dictionary of decoders. Reviewers suggested further performance optimizations, including removing redundant integer conversions for IntEnum keys in _get_type_decoder, and using zip with sliced lists in _append_to_current_row and _decode_eager_rows to avoid the overhead of index lookups and enumeration.
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🤖 I have created a release *beep* *boop* --- ## [3.72.0](google-cloud-spanner-v3.71.0...google-cloud-spanner-v3.72.0) (2026-11-12) ### Features * **dbapi:** wire timeout parameter through Connection to execute_sql ([#18484](#18484)) ([98fc304](98fc304)) * declare Python3.15 support ([8775794](8775794)) * **spanner:** auth login support for Spanner Omni endpoints ([#18273](#18273)) ([9e0548d](9e0548d)) * update API sources and regenerate ([#18797](#18797)) ([be4d954](be4d954)) ### Bug Fixes * **google-cloud-spanner:** clear buffered DDL statements on rollback and flush on autocommit ([#18636](#18636)) ([15d6a2c](15d6a2c)) * **google-cloud-spanner:** do not replay DDL statements on transaction retry ([#18625](#18625)) ([78b9da2](78b9da2)) * **spanner:** correctly wrap async streaming calls in metrics interceptor ([#18581](#18581)) ([2d19b0a](2d19b0a)) * **spanner:** eliminate duplicate metrics capture and measure full streaming latency ([#18605](#18605)) ([a7678fd](a7678fd)) * **spanner:** record streaming operation completion when stream finishes ([#18704](#18704)) ([ddeae47](ddeae47)) * **spanner:** release transaction lock if inline begin fails ([#18409](#18409)) ([dd24029](dd24029)) * **spanner:** stop deleting multiplexed sessions on rotation and close ([#18332](#18332)) ([c38e960](c38e960)) ### Performance Improvements * **spanner:** add fast-path for multiplexed session acquisition ([#18317](#18317)) ([9569b39](9569b39)) * **spanner:** avoid allocating empty RequestOptions on read and query paths ([#18422](#18422)) ([3743ff0](3743ff0)) * **spanner:** build ExecuteSqlRequest on the raw protobuf message ([#18379](#18379)) ([6d91fec](6d91fec)) * **spanner:** eliminate redundant tracing span in run_in_transaction ([#18357](#18357)) ([181e26a](181e26a)) * **spanner:** optimize built-in metrics hot path and harden concurrency ([#18329](#18329)) ([f2a791f](f2a791f)) * **spanner:** optimize query option merging and prevent in-place mutation ([#18358](#18358)) ([8cb3c6a](8cb3c6a)) * **spanner:** optimize query parameter encoding with direct type dispatch ([#18359](#18359)) ([f06497c](f06497c)) * **spanner:** optimize query result decoding and type resolution ([#18330](#18330)) ([ce72986](ce72986)) * **spanner:** optimize request ID header generation and retry closures ([#18408](#18408)) ([ad03b95](ad03b95)) * **spanner:** optimize row popping in StreamedResultSet ([#18316](#18316)) ([e66103d](e66103d)) * **spanner:** optimize single-chunk results and single-row lookups ([#18602](#18602)) ([05b3775](05b3775)) * **spanner:** prune lock and begin event allocations on single-use snapshots ([#18420](#18420)) ([ab56473](ab56473)) * **spanner:** short-circuit trace_call when tracing is inactive ([#18356](#18356)) ([58031be](58031be)) * **spanner:** support PartialResultSet.last with background stream draining ([#18320](#18320)) ([80efd63](80efd63)) ### Documentation * fix typos ([#18979](#18979)) ([5c8baeb](5c8baeb)) --- This PR was generated with [Release Please](https://github.com/googleapis/release-please). See [documentation](https://github.com/googleapis/release-please#release-please). Co-authored-by: release-please[bot] <55107282+release-please[bot]@users.noreply.github.com>
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Improve query result decoding performance in StreamedResultSet and simplify type decoder resolution in _helpers.
Benchmark Results: Lazy Decode Performance (Head-to-Head vs
main)We benchmarked this PR branch (
spanner-decode-and-type-resolution) concurrently against the currentmainbranch under identical conditions on Google Compute Engine (n2-standard-2, 2 vCPUs, single worker thread, closed-loop ineurope-north1-a) usinglazy_decode=True.This workload measures pure result set streaming and raw protobuf cell iteration without eager deserialization into rich Python types.
1. Wide Result Set (
read-large-result-set, 100,000 rows/query,lazy_decode=True)main2. Narrow Result Set (
read-narrow-result-set, 200,000 rows/query,lazy_decode=True)mainObservations
lazy_decode=True: Across repeated concurrent head-to-head runs, replacing cell-by-cell Python iteration in_merge_valueswith native C-level list slicing (_decode_lazy_rows) delivers consistent speedups across both wide and narrow workloads:lazy_decode=False), execution is bounded by network streaming and Python object instantiation (datetime,Decimal,json.loads), tracking within ±1% ofmain. When applications uselazy_decode=True, this optimization delivers significant real-world CPU and latency savings.