converter: cast ints to float in float-inferred fields before table build - #132
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…uild JSON producers emit whole floats as integers. PyArrow accepts an int in a double column only when the conversion is exact; an integer above 2^53 makes pa.Table.from_pylist raise ArrowInvalid and the batch crashes before any column coercion runs (session_replay_features carried 130184854372975800 in a mouse aggregate and crash-looped the consumer). Pre-cast ints to float when the inferred field type is floating - nearest-double is the wanted semantics for a floating measure. Int-only fields are untouched and keep exact int64 (existing large-int precision test still passes).
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Problem
session-replay-featurescrash-loops: the topic's float aggregates JSON-serialize as integers when whole, and one record carried130184854372975800(> 2^53) in a double-inferred field.pa.Table.from_pylistrefuses inexact int→double, so the batch crashes insideconvert()— beforecoerce_typed_columnsruns, which is why thetypedColumnspins (PostHog/charts#15010) can't fix this half of the failure.Fix
_floatify_integers_in_float_fields: after schema inference and mixed-type stringification, cast int values tofloat()for fields the schema types as floating. Nearest-double is the intended semantics for floating measures; PyArrow's exactness check is the only obstacle. Int-only fields are untouched (schema infers int64, no cast) — the existingtest_large_integer_precision_preservedguarding >2^53 int precision still passes.Records are only copied when a cast is needed; the common all-float path allocates nothing.
Tests
test_large_int_in_float_field_converts_lossily(the exact prod poison value) andtest_whole_int_in_float_field_stays_float.Deploy
Standard release path: merge → release workflow → Promote-to-prod retag. The session consumers are scaled to zero pending this + the charts pins; re-enable follows both.