Systematic pass through PRG hot paths, promoting them to Go RTL while
preserving Harbour/FiveSql2 semantics. Full log in
docs/RTL-Go-Native-Migration.md.
Bench (bench_sql) vs 2026-04-08 baseline
- B1 SELECT * 2,192 → 114 µs (19x)
- B6 INNER JOIN 9,291 → 233 µs (40x)
- B7 CTE simple 8,037 → 129 µs (62x)
- B9 ROW_NUMBER 3,705 → 265 µs (14x)
- B10 RANK PARTITION 4,748 → 309 µs (15x)
- B12 INSERT (WA cache) 4,319 → 63 µs (69x)
- B13 UPDATE (WA cache) 6,144 → 68 µs (90x)
- B15 CTE+WIN+JOIN 18,395 → 1,873 µs (10x)
Infrastructure
- HbHash O(1) Index preserving insertion order (Harbour KEEPORDER)
- HbDeepClone Go RTL (scalar-sharing, immutable hash keys)
- MEMRDD auto-imported via gengo; all Five programs get mem:name driver
- SQL plan + pcode caches (s_hPlanCache, s_hDmlPcodeCache)
- Opt-in SqlWACacheEnable — dbUseArea/Close/Commit batched for DML
SQL engine
- FiveSql2 lexer ported to Go (byte FSM) with combined automatic
template parameterization (literals → ?, concat queries share plan)
- Go RTL: SqlDistinct, SqlGroupRows, SqlWindowPartitions,
SqlWindowSortPartition, SqlWindowAssignRank, SqlComputeAggSimple,
SqlBulkInsert, SqlBulkUpdate, SqlExprHasAgg, SqlEvalHaving
- CTE / subquery / driving-table materialize paths use MEMRDD
- SqlCoerce/SqlCmp/SqlIsTrue helpers moved from PRG to Go
- SqlBulkUpdate defers Flush when WA cache active (APFS fsync was
dominant B13 cost — 1.6ms/call → gone)
Correctness fixes uncovered during migration
- ASort default path now sorts dates/logicals/timestamps (was no-op)
- ORDER BY default NULL placement matches PRG SqlRowCompare across
Go fast path; explicit NULLS FIRST/LAST honored by both paths
- SqlBulkUpdate respects EXCLUSIVE vs SHARED mode record locks
- SqlCmp/SqlCmpEq normalize NumInt vs Double (caught by test 6b)
Verification
- go test ./... ALL PASS
- FiveSql2 test_sql1999 43/43
- tests/compat_harbour 56/56 (+5 new: ASort dates/logicals,
AScan int cross-type)
- Regression test test_null_order.prg for ORDER BY NULL ordering
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
107 lines
2.7 KiB
Plaintext
107 lines
2.7 KiB
Plaintext
// Prepared-statement vs concatenated-SQL benchmark.
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// Demonstrates the plan cache win for parameterized queries — the same
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// `?` template hits cache on every call after the first; concatenated
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// SQL strings vary by value and miss every time.
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#include "FiveSqlDef.ch"
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#define ITERS 1000
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PROCEDURE Main()
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LOCAL t0, t1, i
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ErrorBlock( {|e| QOut( "TRAP: " + e:description + " " + e:operation ), Break(e) } )
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? "================================================================"
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? " FiveSql2 Prepared-Statement Benchmark"
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? " " + hb_ntos( ITERS ) + " iterations per pattern"
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? "================================================================"
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?
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SetupTable()
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/* A: concatenated INSERT — SQL text changes per iteration, every
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* call misses the plan cache and re-parses. */
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t0 := hb_MilliSeconds()
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FOR i := 1 TO ITERS
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five_SQL( "INSERT INTO bench_prep (id, val) VALUES (" + hb_ntos( i ) + ", 'a')" )
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NEXT
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t1 := hb_MilliSeconds()
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R( "CONCAT_INSERT", t1 - t0 )
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TruncateTable()
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/* B: prepared INSERT — same SQL text every iteration, cache hits
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* from the 2nd call onward. */
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t0 := hb_MilliSeconds()
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FOR i := 1 TO ITERS
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five_SQL( "INSERT INTO bench_prep (id, val) VALUES (?, ?)", { i, "a" } )
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NEXT
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t1 := hb_MilliSeconds()
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R( "PREPARED_INSERT", t1 - t0 )
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TruncateTable()
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/* C: concatenated SELECT by id. */
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t0 := hb_MilliSeconds()
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FOR i := 1 TO ITERS
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five_SQL( "SELECT val FROM bench_prep WHERE id = " + hb_ntos( i ) )
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NEXT
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t1 := hb_MilliSeconds()
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R( "CONCAT_SELECT", t1 - t0 )
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/* D: prepared SELECT by id. */
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t0 := hb_MilliSeconds()
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FOR i := 1 TO ITERS
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five_SQL( "SELECT val FROM bench_prep WHERE id = ?", { i } )
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NEXT
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t1 := hb_MilliSeconds()
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R( "PREPARED_SELECT", t1 - t0 )
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CleanupTable()
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?
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? "================================================================"
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RETURN
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STATIC PROCEDURE SetupTable()
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IF hb_FileExists( "bench_prep.dbf" )
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FErase( "bench_prep.dbf" )
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ENDIF
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dbCreate( "bench_prep.dbf", { ;
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{ "ID", "N", 10, 0 }, ;
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{ "VAL", "C", 10, 0 } ;
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} )
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/* Pre-populate enough rows so SELECT benchmark has real data. */
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USE bench_prep.dbf NEW EXCLUSIVE
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LOCAL i
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FOR i := 1 TO ITERS
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dbAppend()
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FieldPut( 1, i )
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FieldPut( 2, "a" )
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NEXT
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dbCommit()
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CLOSE bench_prep
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RETURN
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STATIC PROCEDURE TruncateTable()
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USE bench_prep.dbf NEW EXCLUSIVE
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dbZap()
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CLOSE bench_prep
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RETURN
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STATIC PROCEDURE CleanupTable()
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dbCloseAll()
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FErase( "bench_prep.dbf" )
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RETURN
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STATIC FUNCTION R( cLabel, nMs )
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? " ", PadR( cLabel, 18 ) + Str( nMs, 7 ) + " ms " + ;
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Str( nMs * 1000 / ITERS, 8, 2 ) + " us/query"
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RETURN NIL
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