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Choose fail semantics for non-negotiable constraints. This design action addresses a different case (expectation fail action), where the pipeline continues despite critical null records. Fail-on-violation expectations stop updates rather than silently filtering rows. In the stated problem, a plain dropDuplicates retains state without a practical bound for never-ending keys; this choice would not establish the required streaming dedup watermark decision.

Rank events by business key, event time and a deterministic tie-breaker. This design action addresses a different case (latest-per-key with ties), where two events have the same event time and yield different surviving rows. A deterministic tie-breaker is required in a per-key window ranking. In the stated problem, a plain dropDuplicates retains state without a practical bound for never-ending keys; this choice would not establish the required streaming dedup watermark decision.

Use a left join plus a documented fallback label for unmatched keys. This design action addresses a different case (conditional enrichment), where an unconditional inner join discards rows with missing region codes. A left join with explicit CASE logic preserves rows while enriching those that match. In the stated problem, a plain dropDuplicates retains state without a practical bound for never-ending keys; this choice would not establish the required streaming dedup watermark decision.

Inspect input size variation and worker utilization over time. This diagnose action addresses a different case (autoscaling right-size), where a fixed high-worker count wastes resources on quiet days. Supported autoscaling can adapt worker count within configured bounds. In the stated problem, executor memory pressure grows even though input rate is stable; this choice would not establish the required streaming state growth decision.

Inspect file count and size distribution before tuning. This diagnose action addresses a different case (small file compaction), where read overhead grows because query plans open excessive small files. OPTIMIZE can compact compatible Delta files without changing logical table contents. In the stated problem, executor memory pressure grows even though input rate is stable; this choice would not establish the required streaming state growth decision.

Inspect repeated lineage and memory availability for the reference data. This diagnose action addresses a different case (cache reuse), where repeated recomputation dominates each branch's execution. Persistence can avoid repeated work if reused data fits the memory budget. In the stated problem, executor memory pressure grows even though input rate is stable; this choice would not establish the required streaming state growth decision.

Define freshness SLO based on end-to-end observed lag. This design action addresses a different case (end-to-end sla), where operators monitor compute uptime rather than data freshness. SLA monitoring should measure source event time to published table availability. In the stated problem, consumer lag grows while microbatch intervals appear stable; this choice would not establish the required streaming backlog decision.

Define a stable fingerprint and runtime baseline for the query. This design action addresses a different case (sql query history), where no baseline is available for the warehouse query execution. Query history/system query records support comparison of execution time and workload. In the stated problem, consumer lag grows while microbatch intervals appear stable; this choice would not establish the required streaming backlog decision.

Report violation rate as an explicit quality indicator. This design action addresses a different case (expectation monitoring), where analysts confuse successful pipeline status with zero rejected records. Quality metric events reveal input and dropped records separately from update status. In the stated problem, consumer lag grows while microbatch intervals appear stable; this choice would not establish the required streaming backlog decision.

Inspect pip resolution output and the installed dependency tree. This diagnose action addresses a different case (library version pinning), where a transitive dependency updated to an incompatible version. Explicit compatible dependency versions improve reproducibility across new compute environments. In the stated problem, both the normal and repair tasks run despite a branching requirement; this choice would not establish the required conditional task branches decision.

Inspect wheel contents, import paths and the task's installed package version. This diagnose action addresses a different case (python wheel packaging), where a refactor broke a notebook-relative import in the deployed job. A properly packaged versioned wheel gives Python code stable import paths outside notebooks. In the stated problem, both the normal and repair tasks run despite a branching requirement; this choice would not establish the required conditional task branches decision.

Inspect task invocation mode and module entrypoint expectations. This diagnose action addresses a different case (python task entrypoints), where the task exits before setting up its argument parser. A standard Python entrypoint and explicit arguments avoid notebook runtime assumptions. In the stated problem, both the normal and repair tasks run despite a branching requirement; this choice would not establish the required conditional task branches decision.

Inspect run status, task IDs and time windows in supported jobs system tables. This diagnose action addresses a different case (job operational history), where operators only see the most recent run in the Jobs UI. Jobs system records support historical analysis of runs and tasks. In the stated problem, only personal email notifications are configured; this choice would not establish the required job webhook destination decision.

Inspect the unit-coverage query and expected threshold. This diagnose action addresses a different case (sql alert threshold), where the current dashboard has no automated alert for missing units. SQL alerts can evaluate a query result against a configured threshold. In the stated problem, only personal email notifications are configured; this choice would not establish the required job webhook destination decision.

Inspect stage summary, shuffle read sizes and longest task duration. This diagnose action addresses a different case (spark ui shuffle metrics), where operators only monitor cluster-wide CPU and miss skewed task durations. Spark UI stage metrics reveal shuffle, spill and task skew. In the stated problem, only personal email notifications are configured; this choice would not establish the required job webhook destination decision.

Compare normalized outputs including Unicode and null samples. This validate action addresses a different case (avoid python udf for sql), where the Python UDF creates an avoidable cross-language execution boundary. Built-in Spark SQL functions can execute in optimized expressions without Python UDF overhead. In the stated problem, code contains hard-coded region IDs and catalog names; this choice would not establish the required job parameters decision.

Compare outputs on edge cases and measure stage time on representative data. This validate action addresses a different case (vectorized udf), where row-by-row Python invocation dominates stage runtime. Pandas UDFs process batches through Arrow rather than per-row Python calls. In the stated problem, code contains hard-coded region IDs and catalog names; this choice would not establish the required job parameters decision.

Verify production tasks receive the production catalog and input paths. This validate action addresses a different case (bundle target overrides), where development job arguments were deployed into the production target. Bundle targets can override environment-specific variables and resource settings. In the stated problem, code contains hard-coded region IDs and catalog names; this choice would not establish the required job parameters decision.

Plan secret rotation with a new value and safe rollback. This design action addresses a different case (credential rotation procedure), where the hard-coded service password has not rotated for a year. Secret management and controlled rotation reduce long-lived credential exposure. In the stated problem, granting SELECT on the raw fact table violates minimization; this choice would not establish the required secure view sharing decision.

Use a row filter keyed to approved region mapping. This design action addresses a different case (unity catalog row filter), where a shared table currently returns all regions to every reader. Unity Catalog row filters can restrict row visibility through governed policies. In the stated problem, granting SELECT on the raw fact table violates minimization; this choice would not establish the required secure view sharing decision.

Apply a governed column mask while preserving needed analytic access. This design action addresses a different case (column masking), where a raw SELECT on an approved table exposes plaintext email. Unity Catalog column masks can transform sensitive values at read time. In the stated problem, granting SELECT on the raw fact table violates minimization; this choice would not establish the required secure view sharing decision.

Grant only required read privileges on the external location. This implement action addresses a different case (storage credential scope), where engineers propose a credential allowing access to all company buckets. Unity Catalog storage credentials and external locations can constrain storage access. In the stated problem, the team needs read-only access for most users; this choice would not establish the required workspace object acl decision.

Configure the approved network access control for the workspace. This implement action addresses a different case (ip-based workspace restrictions), where a Unity Catalog table grant does not restrict web-console network entry. Workspace access controls and data-object privileges address different security layers. In the stated problem, the team needs read-only access for most users; this choice would not establish the required workspace object acl decision.

Revoke unnecessary production ownership and grant task-specific roles. This implement action addresses a different case (separation of duties), where all developers currently own production catalogs and can grant access. Separate deploy and governance roles reduce accidental privilege escalation. In the stated problem, the team needs read-only access for most users; this choice would not establish the required workspace object acl decision.

Monitor job run arguments for unexpected target or region values. This monitor action addresses a different case (job parameters), where code contains hard-coded region IDs and catalog names. Task parameters allow runtime-specific values without changing notebook source. In the stated problem, development job arguments were deployed into the production target; this choice would not establish the required bundle target overrides decision.

Detect unmanaged changes to deployed job resources. This monitor action addresses a different case (databricks cli resource updates), where production configuration drifts from repository source definitions. Declarative deployment describes resources as reviewed version-controlled artifacts. In the stated problem, development job arguments were deployed into the production target; this choice would not establish the required bundle target overrides decision.

Alert when the deployed checkpoint path differs from baseline. This monitor action addresses a different case (streaming checkpoint identity), where a newly selected checkpoint location makes the stream reread historical input. Streaming checkpoint metadata records progress and state for restart continuity. In the stated problem, development job arguments were deployed into the production target; this choice would not establish the required bundle target overrides decision.

Audit tag removal or changes to sensitive labels. This monitor action addresses a different case (governed tags), where naming conventions alone are inconsistent across teams. Governed tags can classify assets for discovery and policy workflows. In the stated problem, raw cloud permissions bypass central catalog governance; this choice would not establish the required external location governance decision.

Audit unapproved external paths and location changes. This monitor action addresses a different case (managed storage ownership), where the data platform cannot apply consistent lifecycle governance. Managed locations centralize storage ownership for Unity Catalog managed assets. In the stated problem, raw cloud permissions bypass central catalog governance; this choice would not establish the required external location governance decision.

Audit missing-parent-usage failures and overly broad grants. This monitor action addresses a different case (catalog privilege inheritance), where the team lacks USE CATALOG and USE SCHEMA on the parent containers. Unity Catalog object access generally requires relevant parent usage privileges. In the stated problem, raw cloud permissions bypass central catalog governance; this choice would not establish the required external location governance decision.

Restart and confirm previously committed input is not reprocessed unexpectedly. This validate action addresses a different case (streaming checkpoint identity), where a newly selected checkpoint location makes the stream reread historical input. Streaming checkpoint metadata records progress and state for restart continuity. In the stated problem, overwrite-style updates destroy historical state needed for point-in-time reporting; this choice would not establish the required scd type 2 history decision.

Replay update and delete events and confirm one accurate current row per key. This validate action addresses a different case (auto cdc keys), where applying events as append-only rows leaves outdated active accounts. AUTO CDC or applicable APPLY CHANGES needs stable keys and sequence ordering for stateful upserts. In the stated problem, overwrite-style updates destroy historical state needed for point-in-time reporting; this choice would not establish the required scd type 2 history decision.

Confirm dashboard results refresh after source data updates. This validate action addresses a different case (materialized view choice), where each dashboard query recomputes the same expensive aggregation. A materialized view maintains a precomputed query result through refresh. In the stated problem, overwrite-style updates destroy historical state needed for point-in-time reporting; this choice would not establish the required scd type 2 history decision.