Bug triage results: 2026-08-31

Triage pass over the open `requires-triage` queue, per the project [Bug Triage Guide](https://github.com/apache/datafusion-comet/blob/main/docs/source/contributor-guide/bug_triage.md).

- Date: 2026-08-31
- Total issues processed: 77 (73 triaged, 4 skipped, 0 failed)
- Type counts: 24 bugs, 49 enhancements
- Priority counts applied: `priority:critical` 5, `priority:high` 2, `priority:medium` 13, `priority:low` 4
- Guide: [docs/source/contributor-guide/bug_triage.md](https://github.com/apache/datafusion-comet/blob/main/docs/source/contributor-guide/bug_triage.md)

Labels have already been applied. A reviewer should spot-check the calls below and close this issue when satisfied; corrections should be made directly on the affected issue.

Note: where an issue already carried a priority label applied by its author, that label was left in place. Per the guide, this process adds a priority label to bugs only.

## Bugs

### priority:critical

- Checked TIMESTAMP_MILLIS overflow for nested fields and nested-predicate scans is blocked on DataFusion nested-field pruning ([#5553](https://github.com/apache/datafusion-comet/issues/5553))
- Area labels: `area:scan`
- Rationale: nested-field and nested-predicate scans keep overflow-to-NULL where Spark's `Math.multiplyExact` throws, which is a silent wrong result under decision-tree step 1, even though the fix is blocked on upstream nested-field pruning.
- Match Spark ObjectHashAggregate decimal AVG buffer semantics ([#5509](https://github.com/apache/datafusion-comet/issues/5509))
- Area labels: `area:aggregation`
- Rationale: grouped high-precision decimal AVG returns a different value from Spark with no error when Spark uses `ObjectHashAggregateExec`, a silent wrong result.
- Match Spark ordering and rank semantics for floating values nested in arrays and structs ([#5507](https://github.com/apache/datafusion-comet/issues/5507))
- Area labels: `area:expressions`
- Rationale: nested `-0.0`/NaN comparison keys give different `ORDER BY` and `RANK()` output from Spark with no error, a silent wrong result.
- Support Spark-compatible Unicode case-insensitive Parquet field matching ([#5495](https://github.com/apache/datafusion-comet/issues/5495))
- Area labels: `area:scan`
- Rationale: filed as a feature request, but the content is a correctness divergence — the native adapter's ASCII-only `eq_ignore_ascii_case` can miss a present physical column and return SQL NULL instead of the stored value under `spark.sql.caseSensitive=false`.
- Date-to-timestamp casts can overflow or panic for wide dates ([#5456](https://github.com/apache/datafusion-comet/issues/5456))
- Area labels: `area:expressions`
- Rationale: unchecked multiplication wraps to a bogus timestamp in release builds where Spark throws, which is a silent wrong result; the second reproducer additionally panics.

### priority:high

- Native Azure store lets ambient AZURE_* environment variables override or corrupt explicit Hadoop auth config ([#5542](https://github.com/apache/datafusion-comet/issues/5542))
- Area labels: `area:scan`
- Rationale: ambient env credentials silently win over explicitly configured Hadoop auth, so Comet and Spark can resolve different identities for the same table; major functional breakage with a security dimension.
- Iceberg native scan claims schemes it cannot execute; three scheme lists disagree ([#5541](https://github.com/apache/datafusion-comet/issues/5541))
- Area labels: `area:scan`
- Rationale: a `gcs`/`abfs`/`abfss`/`wasb`/`wasbs` Iceberg table passes validation, is claimed, and then every task dies with `CometNativeException`, while stock Spark reads it fine — major functional breakage on supported storage.

### priority:medium

- Fix remaining reported issues for arrays of map ([#5544](https://github.com/apache/datafusion-comet/issues/5544))
- Area labels: `area:expressions`
- Rationale: post-merge review of #5452 (merged) finds newly admitted complex literals and a `deepNullable` cast that changes Slice's nested map type while Slice still declares the original element type; a functional bug with a fallback workaround.
- Iceberg native scan fails queries on tables whose column names are case-distinct to Java but not to Rust ([#5540](https://github.com/apache/datafusion-comet/issues/5540))
- Area labels: `area:scan`
- Rationale: Rust's newer Unicode data folds columns Java keeps distinct, so the query dies with `_LEGACY_ERROR_TEMP_2093` — visible breakage with a fallback workaround.
- Native Celeborn shuffle: validate_remote_schema rejects dictionary shapes the shuffle writer can emit ([#5536](https://github.com/apache/datafusion-comet/issues/5536))
- Area labels: `area:shuffle`
- Rationale: local and remote readers disagree about valid frames, so a frame that reads locally fails on Celeborn; a broken feature, and the path is not yet enabled end to end.
- NativeUtil.getNextBatch leaks Arrow structs when importVector fails ([#5534](https://github.com/apache/datafusion-comet/issues/5534))
- Area labels: `area:ffi`, `area:shuffle`
- Rationale: the third exit from `getNextBatch` is unguarded, leaking C data and wrapper buffers on every native operator path; resource exhaustion rather than wrong results or an immediate crash.
- unbase64 can fail on rows skipped by LIMIT and semi/anti joins ([#5532](https://github.com/apache/datafusion-comet/issues/5532))
- Area labels: `area:expressions`
- Rationale: batch-at-a-time evaluation turns a query Spark completes into a decode failure; a visible functional bug with an expression-level opt-out.
- Native Celeborn shuffle: the installed Celeborn bootstrap hook can break client creation for the whole executor ([#5529](https://github.com/apache/datafusion-comet/issues/5529))
- Area labels: `area:shuffle`
- Rationale: a Comet-specific bootstrap failure is fatal to all Celeborn client creation on the executor; scoped medium because the native Celeborn path is not enabled end to end yet (see escalations).
- Native Celeborn shuffle: reflectively replacing Celeborn's final fields can release push admission while payloads are in flight ([#5528](https://github.com/apache/datafusion-comet/issues/5528))
- Area labels: `area:shuffle`
- Rationale: reflective assignment to four `private final` Celeborn fields can release admission early; a broken feature on a path that is not yet enabled.
- Native Celeborn shuffle: default maxFrameBytes of 64 MiB is unreachable, and a large row fails the whole job ([#5527](https://github.com/apache/datafusion-comet/issues/5527))
- Area labels: `area:shuffle`
- Rationale: the two shipped defaults cannot both hold, and the consequence for a large row is a failed job rather than a slow one; configurable, so a workaround exists.
- Comet native broadcast fails under spark.kryo.registrationRequired=true ([#5510](https://github.com/apache/datafusion-comet/issues/5510))
- Area labels: none
- Rationale: `Array[ChunkedByteBuffer]` is unregistered so broadcast throws outright; broken feature, worked around by not setting that Kryo option.
- Avoid object-store cache and registry collisions across backends and configurations ([#5502](https://github.com/apache/datafusion-comet/issues/5502))
- Area labels: `area:scan`
- Rationale: the cache key omits the backend, so a second URL can be served the first URL's store and the DataFusion registry can replace a mapping; a functional bug reachable only with mixed `fs.comet.libhdfs.schemes` routing.
- Large-offset Arrow vectors from PyArrow UDFs cannot be serialized for broadcast or collect ([#5488](https://github.com/apache/datafusion-comet/issues/5488))
- Area labels: `area:ffi`
- Rationale: `Utils.getFieldVector` throws `Unsupported Arrow Vector for serialize` for representations Comet deliberately produces elsewhere; visible failure on a narrow path.
- AQE + DPP + spark.comet.exec.transitionRevert.enabled fails with "SubqueryAdaptiveBroadcastExec does not support the execute() code path" ([#5486](https://github.com/apache/datafusion-comet/issues/5486))
- Area labels: none
- Rationale: reversion leaves the plan in a state where `PlanAdaptiveDynamicPruningFilters` no longer matches, failing the query; gated on a non-default config, so a workaround exists.
- CometExecRule overwrites direct AQE LogicalQueryStage links during replanning ([#5482](https://github.com/apache/datafusion-comet/issues/5482))
- Area labels: none
- Rationale: unconditional restoration of `originalPlan.logicalLink` breaks the correspondence between the current physical root and the active logical stage; a planner defect with no reported wrong-result or crash path.

### priority:low

- Surface Parquet TIMESTAMP_MILLIS overflow as a Spark-faithful exception instead of a raw Arrow error ([#5517](https://github.com/apache/datafusion-comet/issues/5517))
- Area labels: `area:scan`
- Rationale: the value is correctly rejected, only the exception type and message diverge from Spark's `ArithmeticException("long overflow")`; error-fidelity, no wrong results.
- Cancel background batch producers before collecting final plan metrics ([#5504](https://github.com/apache/datafusion-comet/issues/5504))
- Area labels: `area:ffi`
- Rationale: a drop-time metric guard can update counters after the final snapshot, so the reported metrics are incomplete; observability only.
- Explain ObjectHashAggregate fallback when Comet shuffle is disabled ([#5500](https://github.com/apache/datafusion-comet/issues/5500))
- Area labels: `area:aggregation`
- Rationale: the shuffle guard bypasses `withFallbackReason`, so the strict check can report an unannotated decline; a diagnostics gap, not an execution defect.
- Track provenance of fallback reasons copied through shared expression nodes ([#5499](https://github.com/apache/datafusion-comet/issues/5499))
- Area labels: `area:expressions`
- Rationale: a stale `FALLBACK_REASONS` tag on a shared node can satisfy `reportUnexplainedFallback` and hide an unexplained fallback; diagnostics only.

## Enhancements

- Derive a native UDF's return type from the library instead of requiring the caller to declare it ([#5597](https://github.com/apache/datafusion-comet/issues/5597))
- Area labels: `area:udf` (pre-existing)
- Rationale: an API ergonomics improvement to the native UDF registration surface; nothing is broken today.
- Align Comet's native UDF surface with SPARK-55278's language-agnostic UDF protocol ([#5596](https://github.com/apache/datafusion-comet/issues/5596))
- Area labels: `area:udf` (pre-existing)
- Rationale: forward-looking alignment with an accepted SPIP targeting Spark 4.3/4.4.
- Rename the .claude directory to a vendor-neutral .ai ([#5592](https://github.com/apache/datafusion-comet/issues/5592))
- Area labels: none
- Rationale: repository layout change matching `apache/datafusion` and `apache/datafusion-python`; no functional impact.
- `next_day` and `levenshtein` fall back to Spark on collated strings ([#5591](https://github.com/apache/datafusion-comet/issues/5591))
- Area labels: `area:expressions`
- Rationale: part of #5572; the current fallback is correct, the request is to route it through the codegen dispatcher instead.
- `map_sort` falls back to Spark for non-scalar map key types ([#5590](https://github.com/apache/datafusion-comet/issues/5590))
- Area labels: `area:expressions`
- Rationale: part of #5572; widening dispatcher coverage, not a defect.
- `map_from_arrays` falls back to Spark under `mapKeyDedupPolicy=LAST_WIN`, unlike `map_from_entries` ([#5589](https://github.com/apache/datafusion-comet/issues/5589))
- Area labels: `area:expressions`
- Rationale: part of #5572; requests a `CodegenDispatchFallback` mixin for parity with a sibling serde.
- `timestamp_seconds` falls back to Spark for decimal, byte and short input ([#5588](https://github.com/apache/datafusion-comet/issues/5588))
- Area labels: `area:expressions`
- Rationale: part of #5572; new input-type coverage.
- `abs` on interval types falls back to Spark ([#5587](https://github.com/apache/datafusion-comet/issues/5587))
- Area labels: `area:expressions`
- Rationale: part of #5572; new input-type coverage, already flagged `good first issue`.
- `named_struct` with duplicate field names falls back to Spark ([#5586](https://github.com/apache/datafusion-comet/issues/5586))
- Area labels: `area:expressions`
- Rationale: part of #5572; documented fallback, request is to dispatch instead.
- `translate` falls back to Spark by default instead of using the codegen dispatcher like the other string functions ([#5585](https://github.com/apache/datafusion-comet/issues/5585))
- Area labels: `area:expressions`
- Rationale: part of #5572; the `Incompatible` marking is correct, the ask is dispatcher coverage.
- `length` / `bit_length` / `octet_length` fall back to Spark on binary input ([#5584](https://github.com/apache/datafusion-comet/issues/5584))
- Area labels: `area:expressions`
- Rationale: part of #5572; new input-type coverage.
- `arrays_zip` falls back to Spark for map element types ([#5583](https://github.com/apache/datafusion-comet/issues/5583))
- Area labels: `area:expressions`
- Rationale: part of #5572; new element-type coverage.
- Array functions fall back to Spark for binary and struct element types (`ArraysBase` type gate) ([#5582](https://github.com/apache/datafusion-comet/issues/5582))
- Area labels: `area:expressions`
- Rationale: part of #5572; widening a type gate across seven serdes.
- Hash functions fall back to Spark for decimal precision > 18, and `sha2` for a non-literal `numBits` ([#5581](https://github.com/apache/datafusion-comet/issues/5581))
- Area labels: `area:expressions`
- Rationale: part of #5572; a performance/coverage gap, the fallback itself is correct.
- Map lookups with float, collated or complex keys fall back to Spark (`map_col[key]`, `element_at`) ([#5580](https://github.com/apache/datafusion-comet/issues/5580))
- Area labels: `area:expressions`
- Rationale: part of #5572; the gate exists for real semantic reasons, the ask is to dispatch rather than fall back.
- `lpad` / `rpad` with a non-literal `pad` argument falls back to Spark ([#5579](https://github.com/apache/datafusion-comet/issues/5579))
- Area labels: `area:expressions`
- Rationale: part of #5572; coverage for an ordinary query shape.
- `to_csv` never runs inside Comet by default, unlike `to_json` / `from_csv` / `schema_of_csv` ([#5578](https://github.com/apache/datafusion-comet/issues/5578))
- Area labels: `area:expressions`
- Rationale: part of #5572; coverage plus a documentation update.
- `unix_timestamp` on string input falls back to Spark, while `to_unix_timestamp` already uses the codegen dispatcher ([#5577](https://github.com/apache/datafusion-comet/issues/5577))
- Area labels: `area:expressions`
- Rationale: part of #5572; parity with an equivalent serde.
- `round` on float/double falls back to Spark, while `bround` already uses the codegen dispatcher ([#5576](https://github.com/apache/datafusion-comet/issues/5576))
- Area labels: `area:expressions`
- Rationale: part of #5572; parity with an equivalent serde.
- Route unrecognized `StaticInvoke` and `Invoke` through the codegen dispatcher instead of falling back ([#5575](https://github.com/apache/datafusion-comet/issues/5575))
- Area labels: `area:expressions`
- Rationale: part of #5572; turns a hard fallback default into in-pipeline execution.
- Codegen dispatcher is unreachable from `convert`, so serdes that decline there never get a dispatch attempt ([#5574](https://github.com/apache/datafusion-comet/issues/5574))
- Area labels: `area:expressions`
- Rationale: part of #5572; a structural gap in dispatcher reach rather than incorrect output.
- Codegen dispatcher: guard the closure-serialize step so a non-serializable tree falls back cleanly instead of throwing at plan time ([#5573](https://github.com/apache/datafusion-comet/issues/5573))
- Area labels: `area:expressions`
- Rationale: part of #5572; hardening an unexercised failure mode with no reported occurrence.
- [EPIC] Codegen-dispatch coverage audit: expressions that fall back to Spark where the JVM dispatcher would work ([#5572](https://github.com/apache/datafusion-comet/issues/5572))
- Area labels: `area:expressions`
- Rationale: umbrella for the coverage work above; a performance and coverage effort.
- Narrow the invalid-UTF-8 Comet opt-out in the sketch and hll SQL test files ([#5571](https://github.com/apache/datafusion-comet/issues/5571))
- Area labels: `area:scan`
- Rationale: the opt-out is correct but coarser than the problem; test-coverage improvement.
- SQLQueryTestSuite.ignoreList entries skip the Spark baseline, not just Comet ([#5570](https://github.com/apache/datafusion-comet/issues/5570))
- Area labels: `area:ci`
- Rationale: an intentional exclusion that is coarser than intended; narrowing it restores coverage rather than fixing a failure.
- Remove stale dev/diffs test exclusions whose tracking issues are closed ([#5569](https://github.com/apache/datafusion-comet/issues/5569))
- Area labels: `area:ci`
- Rationale: cleanup of exclusions whose cited issues are fixed; restores coverage.
- Native shuffle rejects nested types as hash partitioning keys although the native hasher supports them ([#5566](https://github.com/apache/datafusion-comet/issues/5566))
- Area labels: `area:shuffle`
- Rationale: the current gate is conservative but safe; the ask is to widen it now that nested hashing exists.
- Support useLargeVarTypes in accelerated mapInArrow/mapInPandas ([#5555](https://github.com/apache/datafusion-comet/issues/5555))
- Area labels: none
- Rationale: new configuration coverage for the accelerated Python UDF path.
- [FEATURE] Enable direct top-level Variant projection in ordinary native Parquet scans ([#5551](https://github.com/apache/datafusion-comet/issues/5551))
- Area labels: `area:scan`
- Rationale: new functionality, one of five atomic PRs under #5546.
- [FEATURE] Match Spark physical Parquet semantics for projected Variant columns ([#5550](https://github.com/apache/datafusion-comet/issues/5550))
- Area labels: `area:scan`
- Rationale: new functionality under #5546; the Variant path it constrains is not yet shipped.
- [FEATURE] Normalize marked Variant arrays at the native Parquet boundary ([#5549](https://github.com/apache/datafusion-comet/issues/5549))
- Area labels: `area:scan`
- Rationale: new functionality under #5546.
- [FEATURE] Carry Spark VariantType identity through Comet schema serialization ([#5548](https://github.com/apache/datafusion-comet/issues/5548))
- Area labels: `area:scan`, `area:ffi`
- Rationale: new protobuf and Arrow Field plumbing under #5546.
- [FEATURE] Export complete Arrow Fields through the native FFI boundary ([#5547](https://github.com/apache/datafusion-comet/issues/5547))
- Area labels: `area:ffi`
- Rationale: new FFI capability under #5546; today's exporter is limited, not broken.
- [FEATURE] Native top-level Variant projection from ordinary Parquet ([#5546](https://github.com/apache/datafusion-comet/issues/5546))
- Area labels: `area:scan`
- Rationale: parent tracking issue for re-landing #5407 as five reviewable PRs.
- Native Celeborn shuffle: the remote read path costs up to 4.5x local decode and is unbenchmarked ([#5535](https://github.com/apache/datafusion-comet/issues/5535))
- Area labels: `area:shuffle`
- Rationale: validation is the right call for untrusted bytes; the ask is measurement and optimization.
- Native Celeborn shuffle: add a Celeborn test dependency so the reflection against its internals is verified ([#5530](https://github.com/apache/datafusion-comet/issues/5530))
- Area labels: `area:shuffle`
- Rationale: test-infrastructure improvement.
- Support NullType output types in codegen dispatch ([#5525](https://github.com/apache/datafusion-comet/issues/5525))
- Area labels: `area:expressions`
- Rationale: widening the dispatch type gate for common untyped literals; the current rejection is safe.
- Support Spark's pushed one-field VariantStruct (whole-value pushVariantIntoScan rewrite) in native Parquet scans ([#5519](https://github.com/apache/datafusion-comet/issues/5519))
- Area labels: `area:scan`
- Rationale: new scan capability; the current behavior is an explicit Spark fallback.
- Expose native Parquet scan I/O and read-amplification metrics ([#5508](https://github.com/apache/datafusion-comet/issues/5508))
- Area labels: `area:scan`
- Rationale: new observability counters.
- Narrow strict floating-point admission for corrected scalar sort keys ([#5506](https://github.com/apache/datafusion-comet/issues/5506))
- Area labels: `area:expressions`
- Rationale: admission is conservative but correct after #5469; the ask is to relax it for scalar keys.
- Include days in CalendarInterval hash when Spark 4.3+ is supported (SPARK-58236) ([#5498](https://github.com/apache/datafusion-comet/issues/5498))
- Area labels: `area:expressions`
- Rationale: Comet matches every currently supported Spark version; this is prospective work for a Spark 4.3 profile.
- ci: Prebuild Linux CI images with toolchains and dependencies ([#5490](https://github.com/apache/datafusion-comet/issues/5490))
- Area labels: `area:ci`
- Rationale: build-infrastructure improvement for reliability and setup time.
- Adopt techniques from Spark's ArrowCachedBatchSerializer (SPARK-57268) in Comet's cache format ([#5487](https://github.com/apache/datafusion-comet/issues/5487))
- Area labels: none
- Rationale: records design ideas worth adopting from an upstream implementation of the same idea.
- Cached reads that feed Spark operators are slower than Spark's own cache format ([#5485](https://github.com/apache/datafusion-comet/issues/5485))
- Area labels: none
- Rationale: a performance gap in a new opt-in feature, not a regression against previously shipped behavior.
- Comet cache decode ignores column projection, making narrow reads of wide cached relations slower than Spark ([#5484](https://github.com/apache/datafusion-comet/issues/5484))
- Area labels: none
- Rationale: a design limitation of the new cache serializer from #5051; optimization request.
- Track and remove native Variant compatibility workarounds after upstream fixes ([#5477](https://github.com/apache/datafusion-comet/issues/5477))
- Area labels: `area:scan`
- Rationale: maintenance bookkeeping so intentionally narrow workarounds do not become permanent.
- Remove Variant UTF-16 output rewriting ([#5474](https://github.com/apache/datafusion-comet/issues/5474))
- Area labels: `area:scan`
- Rationale: removal of a correctness-preserving workaround once upstream ordering lands; current behavior is correct.
- Make fair_unified account for spillable consumers ([#5465](https://github.com/apache/datafusion-comet/issues/5465))
- Area labels: none
- Rationale: memory-pool accounting improvement matching DataFusion's `FairSpillPool`; deliberately left out of the focused #5212 fix.
- Track exact SpillWriter page bytes for O(1) memory usage sampling ([#5462](https://github.com/apache/datafusion-comet/issues/5462))
- Area labels: `area:shuffle`
- Rationale: performance follow-up to #5212 finding #12; the correctness fix stays separately scoped.

## Escalations to consider

- Native Azure store lets ambient AZURE_* environment variables override or corrupt explicit Hadoop auth config ([#5542](https://github.com/apache/datafusion-comet/issues/5542))
- The guide lists security vulnerabilities under `priority:critical`. Ambient environment variables silently overriding an explicitly configured service principal (including the AKS workload-identity webhook case, where the configured client secret is dropped) is an identity-selection issue with a security dimension. Filed `priority:high`; a reviewer may want to escalate.
- Date-to-timestamp casts can overflow or panic for wide dates ([#5456](https://github.com/apache/datafusion-comet/issues/5456))
- Matches the guide's escalation trigger in reverse: it both panics (`NaiveDate + TimeDelta overflowed`) and, in release builds, silently wraps to a wrong timestamp. Filed `priority:critical` on the wrong-result path.
- Native Celeborn shuffle: the installed Celeborn bootstrap hook can break client creation for the whole executor ([#5529](https://github.com/apache/datafusion-comet/issues/5529))
- A Comet-specific bootstrap failure is fatal to all Celeborn shuffle on the executor, not just Comet's. Held at `priority:medium` because the native Celeborn path is not enabled end to end yet (see #5535); escalate to `priority:high` once it ships enabled.
- Checked TIMESTAMP_MILLIS overflow for nested fields and nested-predicate scans is blocked on DataFusion nested-field pruning ([#5553](https://github.com/apache/datafusion-comet/issues/5553))
- Filed `priority:critical` on the silent-wrong-result rule, but the fix is blocked on upstream DataFusion nested-field pruning, so the priority reflects impact rather than actionability.

## Skipped — needs more info

- Bug triage results: 2026-08-24 ([#5454](https://github.com/apache/datafusion-comet/issues/5454))
- A prior triage summary, not a bug or an enhancement, so no type label applies. `requires-triage` left in place. Note that pass applied no labels (its token lacked label write access), so its 28 issues were re-triaged in this pass. A reviewer should close it.
- Bug triage results: 2026-08-17 ([#5385](https://github.com/apache/datafusion-comet/issues/5385))
- A prior triage summary awaiting reviewer sign-off; no type label applies and `requires-triage` was left in place.
- Bug triage results: 2026-08-11 ([#5325](https://github.com/apache/datafusion-comet/issues/5325))
- A prior triage summary awaiting reviewer sign-off; no type label applies and `requires-triage` was left in place.
- Bug triage results: 2026-08-03 ([#5231](https://github.com/apache/datafusion-comet/issues/5231))
- A prior triage summary awaiting reviewer sign-off; no type label applies and `requires-triage` was left in place.

Start with docs/source/contributor-guide/bug_triage.md, then spot-check the labels and rationales listed in this issue against the linked affected issues. Done means confirming the triage calls, correcting labels directly on affected issues when needed, and closing #5601 when satisfied.

Written by the indexing model from the issue text.