Phase G0 Day 4 ships ingestd: multipart CSV upload, Arrow schema
inference per ADR-010 (default-to-string on ambiguity), single-pass
streaming CSV → Parquet via pqarrow batched writer (Snappy compressed,
8192 rows per batch), PUT to storaged at content-addressed key
datasets/<name>/<fp_hex>.parquet, register manifest with catalogd.
Acceptance smoke 6/6 PASS including idempotent re-ingest (proves
inference is deterministic — same CSV always produces same fingerprint)
and schema-drift → 409 (proves catalogd's gate fires on ingest traffic).
Schema fingerprint is SHA-256 over (name, type) tuples in header order
using ASCII record/unit separators (0x1e/0x1f) so column names with
commas can't collide. Nullability intentionally NOT in the fingerprint
— a column gaining nulls isn't a schema change.
Cross-lineage scrum on shipped code:
- Opus 4.7 (opencode): 4 WARN + 3 INFO (after 2 self-retracted BLOCKs)
- Kimi K2-0905 (openrouter): 1 BLOCK + 2 WARN + 1 INFO
- Qwen3-coder (openrouter): 2 BLOCK + 2 WARN + 2 INFO
Fixed (2, both Opus single-reviewer):
C-DRIFT: PUT-then-register on fixed datasets/<name>/data.parquet
meant a schema-drift ingest overwrote the live parquet BEFORE
catalogd's 409 fired → storaged inconsistent with manifest.
Fix: content-addressed key datasets/<name>/<fp_hex>.parquet.
Drift writes to a different file (orphan in G2 GC scope); the
live data is never corrupted.
C-WCLOSE: pqarrow.NewFileWriter not Closed on error paths leaks
buffered column data + OS resources per failed ingest.
Fix: deferred guarded close with wClosed flag.
Dismissed (5, all false positives):
Qwen BLOCK "csv.Reader needs LazyQuotes=true for multi-line" — false,
Go csv handles RFC 4180 multi-line quoted fields by default
Qwen BLOCK "row[i] OOB" — already bounds-checked at schema.go:73
and csv.go:201
Kimi BLOCK "type assertion panic if pqarrow reorders fields" —
speculative, no real path
Kimi WARN + Qwen WARN×2 "RecordBuilder leak on early error" —
false convergent. Outer defer rb.Release() captures the current
builder; in-loop release runs before reassignment. No leak.
Deferred (6 INFO + accepted-with-rationale on 3 WARN): sample
boundary type mismatch (G0 cap bounds peak), string-match
paranoia on http.MaxBytesError, multipart double-buffer (G2 spool-
to-disk), separator validation, body close ordering, etc.
The D4 scrum produced fewer real findings than D3 (2 vs 6) — both
were architectural hazards smoke wouldn't catch because the smoke's
"schema drift → 409" assertion was passing even in the corrupted-
state world. The 409 fires correctly; what was wrong was the PUT
having already mutated the live parquet before the validation check.
Opus's PUT-then-register read of the order is exactly the kind of
architectural insight the cross-lineage scrum is designed to surface.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
233 lines
6.3 KiB
Go
233 lines
6.3 KiB
Go
// csv.go — single-pass CSV → Arrow → Parquet streaming pipeline.
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// Buffers the first N data rows for schema inference, then writes
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// those rows + every subsequent row directly into the pqarrow writer
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// in record batches of BatchSize. Output is the encoded Parquet
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// payload + the inferred schema + total row_count.
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package ingestd
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import (
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"bytes"
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"encoding/csv"
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"errors"
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"fmt"
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"io"
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"strconv"
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"github.com/apache/arrow-go/v18/arrow"
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"github.com/apache/arrow-go/v18/arrow/array"
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"github.com/apache/arrow-go/v18/arrow/memory"
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"github.com/apache/arrow-go/v18/parquet"
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"github.com/apache/arrow-go/v18/parquet/compress"
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"github.com/apache/arrow-go/v18/parquet/pqarrow"
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)
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// DefaultBatchSize is the per-record-batch row count fed to the
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// pqarrow writer. 8192 is the Arrow community default — large
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// enough to amortize per-batch overhead, small enough to keep peak
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// memory bounded for very wide CSVs.
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const DefaultBatchSize = 8192
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// IngestResult is what IngestCSV returns to the caller. Parquet
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// holds the full encoded payload — fits in memory by design (G0
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// CSVs are <1 GB; storaged caps PUT at 256 MiB; the gap will
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// resurface if/when we hit it).
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type IngestResult struct {
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Schema Schema
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Parquet []byte
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RowCount int64
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}
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// IngestCSV reads CSV from r, infers the schema from the first
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// SampleRows data rows, and streams the entire CSV (sample + rest)
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// into a Parquet payload using the inferred schema.
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//
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// sampleRows ≤ 0 → DefaultSampleRows; batchSize ≤ 0 → DefaultBatchSize.
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//
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// The CSV is read once. The sample rows are held in memory only
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// until they're flushed to the writer; subsequent rows stream
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// through the per-column Arrow builders one batch at a time.
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func IngestCSV(r io.Reader, sampleRows, batchSize int) (*IngestResult, error) {
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if sampleRows <= 0 {
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sampleRows = DefaultSampleRows
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}
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if batchSize <= 0 {
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batchSize = DefaultBatchSize
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}
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cr := csv.NewReader(r)
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cr.FieldsPerRecord = -1 // tolerate ragged rows; trailing-empty cells become nulls
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header, err := cr.Read()
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if err != nil {
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if errors.Is(err, io.EOF) {
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return nil, errors.New("ingestd: CSV is empty (no header)")
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}
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return nil, fmt.Errorf("read header: %w", err)
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}
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// Buffer up to sampleRows for schema inference. Buffered rows
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// are also written to the Parquet output — no double-read.
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buffered := make([][]string, 0, sampleRows)
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for len(buffered) < sampleRows {
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row, err := cr.Read()
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if errors.Is(err, io.EOF) {
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break
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}
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if err != nil {
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return nil, fmt.Errorf("read row %d: %w", len(buffered)+1, err)
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}
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buffered = append(buffered, row)
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}
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schema, err := InferSchema(header, buffered)
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if err != nil {
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return nil, err
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}
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arrowSchema := schema.ArrowSchema()
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mem := memory.NewGoAllocator()
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var buf bytes.Buffer
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props := parquet.NewWriterProperties(
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parquet.WithCompression(compress.Codecs.Snappy),
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)
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w, err := pqarrow.NewFileWriter(arrowSchema, &buf, props, pqarrow.NewArrowWriterProperties())
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if err != nil {
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return nil, fmt.Errorf("pqarrow writer: %w", err)
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}
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// Per scrum C-WCLOSE (Opus WARN): writer holds buffered column
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// data + OS resources; every error return path past this point
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// must close it, otherwise long-running ingestd leaks per failed
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// ingest. closeOnce guards the success-path explicit Close from
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// double-firing.
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wClosed := false
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defer func() {
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if !wClosed {
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_ = w.Close()
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}
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}()
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// Build a fresh RecordBuilder for each batch — flush, release, repeat.
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rowsTotal := int64(0)
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flush := func(rb *array.RecordBuilder) error {
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rec := rb.NewRecord()
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defer rec.Release()
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return w.Write(rec)
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}
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rb := array.NewRecordBuilder(mem, arrowSchema)
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defer rb.Release()
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rowsInBatch := 0
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appendRow := func(row []string) error {
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if err := appendRowToBuilders(rb, schema, row); err != nil {
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return err
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}
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rowsInBatch++
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rowsTotal++
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if rowsInBatch >= batchSize {
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if err := flush(rb); err != nil {
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return err
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}
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rb.Release()
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rb = array.NewRecordBuilder(mem, arrowSchema)
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rowsInBatch = 0
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}
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return nil
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}
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// Replay buffered (already-read) rows into the writer first.
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for _, row := range buffered {
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if err := appendRow(row); err != nil {
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return nil, fmt.Errorf("buffered row: %w", err)
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}
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}
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// Then drain the rest of the CSV.
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for {
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row, err := cr.Read()
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if errors.Is(err, io.EOF) {
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break
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}
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if err != nil {
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return nil, fmt.Errorf("read row %d: %w", rowsTotal+1, err)
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}
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if err := appendRow(row); err != nil {
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return nil, err
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}
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}
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// Flush any partial trailing batch.
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if rowsInBatch > 0 {
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if err := flush(rb); err != nil {
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return nil, fmt.Errorf("flush trailing batch: %w", err)
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}
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}
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if err := w.Close(); err != nil {
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return nil, fmt.Errorf("pqarrow close: %w", err)
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}
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wClosed = true
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return &IngestResult{
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Schema: schema,
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Parquet: buf.Bytes(),
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RowCount: rowsTotal,
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}, nil
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}
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// appendRowToBuilders writes one CSV row's cells into the per-
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// column builders held by rb. Cells beyond the row's width append
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// nulls (ragged-row tolerance). Empty cells append nulls on
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// numeric/bool columns and empty strings on string columns.
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func appendRowToBuilders(rb *array.RecordBuilder, schema Schema, row []string) error {
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for i, col := range schema {
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var cell string
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if i < len(row) {
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cell = row[i]
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}
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fb := rb.Field(i)
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switch col.Type {
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case TypeInt64:
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b := fb.(*array.Int64Builder)
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if cell == "" {
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b.AppendNull()
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continue
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}
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v, err := strconv.ParseInt(cell, 10, 64)
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if err != nil {
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return fmt.Errorf("col %q: %q is not int64: %w", col.Name, cell, err)
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}
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b.Append(v)
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case TypeFloat64:
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b := fb.(*array.Float64Builder)
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if cell == "" {
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b.AppendNull()
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continue
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}
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v, err := strconv.ParseFloat(cell, 64)
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if err != nil {
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return fmt.Errorf("col %q: %q is not float64: %w", col.Name, cell, err)
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}
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b.Append(v)
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case TypeBool:
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b := fb.(*array.BooleanBuilder)
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if cell == "" {
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b.AppendNull()
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continue
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}
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if !isBoolLiteral(cell) {
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return fmt.Errorf("col %q: %q is not bool", col.Name, cell)
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}
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b.Append(cell == "true" || cell == "True" || cell == "TRUE")
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default: // TypeString
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b := fb.(*array.StringBuilder)
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b.Append(cell)
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}
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}
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return nil
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}
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// quiet linter — arrow.Schema is referenced via schema.ArrowSchema()
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// but the import otherwise looks unused on first scan.
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var _ = arrow.NewSchema
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