Reading and Writing Delta Tables with PySpark and SQL

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    Architecture / Concept Overview: Reading and Writing Delta Tables with PySpark and SQL

    %%{init: {"theme":"base","themeVariables":{"background":"#0B0E14","primaryTextColor":"#E0E6ED","lineColor":"#5D6470","darkMode":true,"primaryColor":"#2E4A4A","secondaryColor":"#374151","secondaryTextColor":"#E0E6ED","tertiaryColor":"#111827","tertiaryTextColor":"#E0E6ED","edgeLabelBackground":"#1f2937"}}}%% flowchart LR classDef source fill:#3F4B59,stroke:#9CA3AF,stroke-width:2px,rx:8,ry:8,color:#E0E6ED classDef ingestion fill:#5A4B36,stroke:#C9A86B,stroke-width:2px,rx:8,ry:8,color:#E0E6ED classDef processing fill:#535072,stroke:#8E82B4,stroke-width:2px,rx:8,ry:8,color:#E0E6ED classDef storage fill:#2E4A4A,stroke:#5FAFA8,stroke-width:2px,rx:8,ry:8,color:#E0E6ED classDef serving fill:#3D5550,stroke:#6BB7AA,stroke-width:2px,rx:8,ry:8,color:#E0E6ED classDef governance fill:#5A3F52,stroke:#C28BB0,stroke-width:2px,rx:8,ry:8,color:#E0E6ED SRC[Data Sources] -->|Batch Read| DF[DataFrame] SRC -->|Streaming Read| SS[Structured Streaming] DF -->|append / overwrite| DT[Delta Table] SS -->|micro-batch / continuous| DT DT -->|spark.read| AN[Analysts] DT -->|SQL SELECT| BI[BI Tools] SRC:::source DF:::processing SS:::ingestion DT:::storage AN:::serving BI:::serving

    *Delta tables accept both batch and streaming writes and serve reads through PySpark DataFrames or SQL queries.*

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    *Delta Lake supports multiple write modes and read patterns, each suited to different ingestion and consumption use cases.*

    Key Terms

    Prerequisites and Setup

    • Databricks workspace with a cluster running Databricks Runtime 13.3 LTS or later
    • A Delta table to read from and write to
    • SELECT privilege for reads; MODIFY privilege for writes

    Step-by-Step Implementation

      Configuration Reference

      Reading and Writing Delta Tables with PySpark and SQL configuration options
      PropertyDefaultDescription
      mergeSchemafalseAllows schema evolution during write
      overwriteSchemafalseReplaces the table schema on overwrite
      replaceWhere—Predicate defining which partition(s) to atomically replace
      maxRecordsPerFile—Limits rows per output file for size control
      optimizeWritetrueCoalesces output files for better read performance
      readChangeFeedfalseEnables Change Data Feed streaming reads
      startingVersion—CDF read starting version
      ignoreChangesfalseIgnores data-modifying commits in streaming reads

      Monitoring, Cost, and Security Considerations

      Common Pitfalls and Recommended Patterns

        Frequently Asked Questions