SQL Server Parameter Sniffing: Diagnose It Before You Fix It
A practical guide to finding parameter-sensitive query plans in SQL Server, proving the cause, and choosing the least risky fix.
Read articlePractical articles about ClickHouse, SQL Server, analytics architecture, performance, migration, and database operations.
A practical guide to finding parameter-sensitive query plans in SQL Server, proving the cause, and choosing the least risky fix.
Read articleA job can report success while skipping databases, processing no rows, or finishing too late for downstream work. Final status alone does not prove the intended result.
Read articleSeparate engine migration from compatibility changes, preserve Query Store evidence, and define measurable acceptance and rollback criteria.
Read articleSeparate raw loading, typed validation, and publication so malformed files and retries do not leave production tables partially or incorrectly populated.
Read articleFind where linked-server queries actually execute, push selective work to the remote source, and test semantics, credentials, and failure behavior.
Read articleRead row group states, deleted rows, and trim reasons to explain columnstore performance before changing load batches or scheduling index maintenance.
Read articleBuild an optimistic edit protocol with rowversion, detect conflicting updates, and return useful conflicts without silently overwriting another user's work.
Read articleTemporary tables and table variables both hold intermediate rows, but statistics, compilation, indexing, and transaction behavior can produce very different execution plans.
Read articleCheck the listener, connection intent, replica routing lists, and actual destination before assuming reporting traffic is reaching a readable secondary.
Read articleChoose between changed-key synchronization and captured row history, then design checkpoints, retention monitoring, deletes, and recovery correctly.
Read articleDiagnose backup, copy, and restore lag separately, plan intentional delays, and rehearse a log-shipping failover with a defensible data-loss estimate.
Read articleDiagnose database, column, and tempdb collations, preserve comparison rules, and avoid query fixes that hide index costs or introduce duplicate keys.
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