Curriculum planned

Stage 10 · Lakehouse Table Formats

Apache Iceberg

A comprehensive Apache Iceberg course covering table-format internals, metadata trees, manifests and snapshots, optimistic commits, schema and partition evolution, hidden partitioning, deletes and deletion vectors, row lineage, branching and tagging, catalogs and REST Catalog, Spark/Flink/Trino integrations, PyIceberg, object storage, maintenance, performance, security, disaster recovery, interoperability, and production lakehouse architecture.

Browse planned curriculum Back to all courses

32planned chapters

160reserved lesson paths

Advancedlearning level

Plannedcourse state

Coverage baselineApache Iceberg 1.11.0 baseline (released May 19, 2026), covering format v1/v2/v3 concepts, snapshots and manifests, deletion vectors, row lineage, partition and schema evolution, branching/tagging, REST catalogs and server-side scan planning, Spark/Flink/Trino integration, PyIceberg and multi-language ecosystem awareness, maintenance, governance, and production lakehouse operations

Course brief

Understand Iceberg as a table metadata protocol layered over immutable data files: reason from snapshot isolation, manifests, sequence numbers, partition specs, delete semantics, catalogs, and commit conflicts before tuning engines or automating maintenance.

This syllabus deliberately separates foundations, data/model semantics, internals, reliability, security, performance, operations, and production design so advanced material is not compressed into generic catch-all chapters.

By the end

You will be able to

Explain Iceberg table metadata, snapshots, manifest lists, manifests, data/delete files, sequence numbers, partition specs, sort orders, and optimistic commit semantics
Design tables that evolve schemas and partitioning safely while using time travel, branches/tags, row-level changes, deletes, compaction, and metadata cleanup correctly
Integrate Iceberg with Spark, Flink, Trino and Python-oriented tooling while understanding engine-specific write, catalog, and maintenance behavior
Operate catalogs and object-storage-backed tables with REST Catalog, security, concurrency control, maintenance procedures, observability, and disaster-recovery runbooks
Benchmark and govern production lakehouse designs using explicit file-size, manifest, partition-pruning, delete-file, commit-contention, and metadata-growth evidence

Complete planned syllabus

32 chapters · 160 lesson paths.

Every lesson path is reserved now but intentionally not linked until its lesson HTML is actually published. The sequence moves from foundations through advanced implementation, architecture, operations, reliability, security, tuning, and a production capstone.

Chapter 1

Iceberg Foundations: Open Table Formats, Iceberg 1.11.0, Lakehouse Workloads, Object Storage, and Local Lab Architecture

5 lessons

Iceberg Foundations: Open Table Formats, Iceberg 1.11.0, Lakehouse Workloads, Object Storage, and Local Lab Architecture: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter01/Lesson1.html

Planned02

Iceberg Foundations: Open Table Formats, Iceberg 1.11.0, Lakehouse Workloads, Object Storage, and Local Lab Architecture: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter01/Lesson2.html

Planned03

Iceberg Foundations: Open Table Formats, Iceberg 1.11.0, Lakehouse Workloads, Object Storage, and Local Lab Architecture: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter01/Lesson3.html

Planned04

Iceberg Foundations: Open Table Formats, Iceberg 1.11.0, Lakehouse Workloads, Object Storage, and Local Lab Architecture: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter01/Lesson4.html

Planned05

Checkpoint Lab — Iceberg Foundations: Open Table Formats, Iceberg 1.11.0, Lakehouse Workloads, Object Storage, and Local Lab Architecture: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter01/Lesson5.html

Planned

Chapter 2

Physical Data vs Table Metadata: Parquet/Avro/ORC Files, Immutable Objects, Metadata JSON, Pointer Files, and Atomic Table State

5 lessons

Physical Data vs Table Metadata: Parquet/Avro/ORC Files, Immutable Objects, Metadata JSON, Pointer Files, and Atomic Table State: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter02/Lesson1.html

Planned02

Physical Data vs Table Metadata: Parquet/Avro/ORC Files, Immutable Objects, Metadata JSON, Pointer Files, and Atomic Table State: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter02/Lesson2.html

Planned03

Physical Data vs Table Metadata: Parquet/Avro/ORC Files, Immutable Objects, Metadata JSON, Pointer Files, and Atomic Table State: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter02/Lesson3.html

Planned04

Physical Data vs Table Metadata: Parquet/Avro/ORC Files, Immutable Objects, Metadata JSON, Pointer Files, and Atomic Table State: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter02/Lesson4.html

Planned05

Checkpoint Lab — Physical Data vs Table Metadata: Parquet/Avro/ORC Files, Immutable Objects, Metadata JSON, Pointer Files, and Atomic Table State: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter02/Lesson5.html

Planned

Chapter 3

Metadata Tree Internals: Table Metadata, Snapshot Log, Snapshots, Manifest Lists, Manifests, Entries, and File-Level Statistics

5 lessons

Metadata Tree Internals: Table Metadata, Snapshot Log, Snapshots, Manifest Lists, Manifests, Entries, and File-Level Statistics: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter03/Lesson1.html

Planned02

Metadata Tree Internals: Table Metadata, Snapshot Log, Snapshots, Manifest Lists, Manifests, Entries, and File-Level Statistics: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter03/Lesson2.html

Planned03

Metadata Tree Internals: Table Metadata, Snapshot Log, Snapshots, Manifest Lists, Manifests, Entries, and File-Level Statistics: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter03/Lesson3.html

Planned04

Metadata Tree Internals: Table Metadata, Snapshot Log, Snapshots, Manifest Lists, Manifests, Entries, and File-Level Statistics: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter03/Lesson4.html

Planned05

Checkpoint Lab — Metadata Tree Internals: Table Metadata, Snapshot Log, Snapshots, Manifest Lists, Manifests, Entries, and File-Level Statistics: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter03/Lesson5.html

Planned

Chapter 4

Snapshot Isolation and Optimistic Concurrency: Commits, Base Metadata, Validation, Retries, Conflict Detection, and Concurrent Writers

5 lessons

Snapshot Isolation and Optimistic Concurrency: Commits, Base Metadata, Validation, Retries, Conflict Detection, and Concurrent Writers: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter04/Lesson1.html

Planned02

Snapshot Isolation and Optimistic Concurrency: Commits, Base Metadata, Validation, Retries, Conflict Detection, and Concurrent Writers: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter04/Lesson2.html

Planned03

Snapshot Isolation and Optimistic Concurrency: Commits, Base Metadata, Validation, Retries, Conflict Detection, and Concurrent Writers: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter04/Lesson3.html

Planned04

Snapshot Isolation and Optimistic Concurrency: Commits, Base Metadata, Validation, Retries, Conflict Detection, and Concurrent Writers: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter04/Lesson4.html

Planned05

Checkpoint Lab — Snapshot Isolation and Optimistic Concurrency: Commits, Base Metadata, Validation, Retries, Conflict Detection, and Concurrent Writers: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter04/Lesson5.html

Planned

Chapter 5

Schemas and Field IDs: Add/Drop/Rename/Reorder, Type Promotion, Nested Fields, Identifier Fields, and Evolution without Name-Based Corruption

5 lessons

Schemas and Field IDs: Add/Drop/Rename/Reorder, Type Promotion, Nested Fields, Identifier Fields, and Evolution without Name-Based Corruption: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter05/Lesson1.html

Planned02

Schemas and Field IDs: Add/Drop/Rename/Reorder, Type Promotion, Nested Fields, Identifier Fields, and Evolution without Name-Based Corruption: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter05/Lesson2.html

Planned03

Schemas and Field IDs: Add/Drop/Rename/Reorder, Type Promotion, Nested Fields, Identifier Fields, and Evolution without Name-Based Corruption: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter05/Lesson3.html

Planned04

Schemas and Field IDs: Add/Drop/Rename/Reorder, Type Promotion, Nested Fields, Identifier Fields, and Evolution without Name-Based Corruption: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter05/Lesson4.html

Planned05

Checkpoint Lab — Schemas and Field IDs: Add/Drop/Rename/Reorder, Type Promotion, Nested Fields, Identifier Fields, and Evolution without Name-Based Corruption: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter05/Lesson5.html

Planned

Chapter 6

Hidden Partitioning: Partition Specs, Transforms, Identity/Year/Month/Day/Hour/Bucket/Truncate, and Query Independence from Physical Layout

5 lessons

Hidden Partitioning: Partition Specs, Transforms, Identity/Year/Month/Day/Hour/Bucket/Truncate, and Query Independence from Physical Layout: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter06/Lesson1.html

Planned02

Hidden Partitioning: Partition Specs, Transforms, Identity/Year/Month/Day/Hour/Bucket/Truncate, and Query Independence from Physical Layout: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter06/Lesson2.html

Planned03

Hidden Partitioning: Partition Specs, Transforms, Identity/Year/Month/Day/Hour/Bucket/Truncate, and Query Independence from Physical Layout: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter06/Lesson3.html

Planned04

Hidden Partitioning: Partition Specs, Transforms, Identity/Year/Month/Day/Hour/Bucket/Truncate, and Query Independence from Physical Layout: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter06/Lesson4.html

Planned05

Checkpoint Lab — Hidden Partitioning: Partition Specs, Transforms, Identity/Year/Month/Day/Hour/Bucket/Truncate, and Query Independence from Physical Layout: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter06/Lesson5.html

Planned

Chapter 7

Partition Evolution: Multiple Specs, Historical Files, Spec IDs, Pruning across Evolutions, and Avoiding Expensive Rewrites

5 lessons

Partition Evolution: Multiple Specs, Historical Files, Spec IDs, Pruning across Evolutions, and Avoiding Expensive Rewrites: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter07/Lesson1.html

Planned02

Partition Evolution: Multiple Specs, Historical Files, Spec IDs, Pruning across Evolutions, and Avoiding Expensive Rewrites: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter07/Lesson2.html

Planned03

Partition Evolution: Multiple Specs, Historical Files, Spec IDs, Pruning across Evolutions, and Avoiding Expensive Rewrites: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter07/Lesson3.html

Planned04

Partition Evolution: Multiple Specs, Historical Files, Spec IDs, Pruning across Evolutions, and Avoiding Expensive Rewrites: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter07/Lesson4.html

Planned05

Checkpoint Lab — Partition Evolution: Multiple Specs, Historical Files, Spec IDs, Pruning across Evolutions, and Avoiding Expensive Rewrites: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter07/Lesson5.html

Planned

Chapter 8

Sort Orders and Data Layout: Sort Fields, Transforms, Null/NaN Ordering, Write Distribution, Clustering Effects, and Read Locality

5 lessons

Sort Orders and Data Layout: Sort Fields, Transforms, Null/NaN Ordering, Write Distribution, Clustering Effects, and Read Locality: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter08/Lesson1.html

Planned02

Sort Orders and Data Layout: Sort Fields, Transforms, Null/NaN Ordering, Write Distribution, Clustering Effects, and Read Locality: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter08/Lesson2.html

Planned03

Sort Orders and Data Layout: Sort Fields, Transforms, Null/NaN Ordering, Write Distribution, Clustering Effects, and Read Locality: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter08/Lesson3.html

Planned04

Sort Orders and Data Layout: Sort Fields, Transforms, Null/NaN Ordering, Write Distribution, Clustering Effects, and Read Locality: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter08/Lesson4.html

Planned05

Checkpoint Lab — Sort Orders and Data Layout: Sort Fields, Transforms, Null/NaN Ordering, Write Distribution, Clustering Effects, and Read Locality: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter08/Lesson5.html

Planned

Chapter 9

Snapshots, Time Travel, and Rollback: Snapshot IDs, Timestamps, History, Rollback, Set Current Snapshot, and Reproducible Reads

5 lessons

Snapshots, Time Travel, and Rollback: Snapshot IDs, Timestamps, History, Rollback, Set Current Snapshot, and Reproducible Reads: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter09/Lesson1.html

Planned02

Snapshots, Time Travel, and Rollback: Snapshot IDs, Timestamps, History, Rollback, Set Current Snapshot, and Reproducible Reads: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter09/Lesson2.html

Planned03

Snapshots, Time Travel, and Rollback: Snapshot IDs, Timestamps, History, Rollback, Set Current Snapshot, and Reproducible Reads: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter09/Lesson3.html

Planned04

Snapshots, Time Travel, and Rollback: Snapshot IDs, Timestamps, History, Rollback, Set Current Snapshot, and Reproducible Reads: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter09/Lesson4.html

Planned05

Checkpoint Lab — Snapshots, Time Travel, and Rollback: Snapshot IDs, Timestamps, History, Rollback, Set Current Snapshot, and Reproducible Reads: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter09/Lesson5.html

Planned

Chapter 10

Branches and Tags: Write-Audit-Publish, Experimentation, Retention Policies, Branch Writes, Tagging Releases, and Promotion Workflows

5 lessons

Branches and Tags: Write-Audit-Publish, Experimentation, Retention Policies, Branch Writes, Tagging Releases, and Promotion Workflows: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter10/Lesson1.html

Planned02

Branches and Tags: Write-Audit-Publish, Experimentation, Retention Policies, Branch Writes, Tagging Releases, and Promotion Workflows: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter10/Lesson2.html

Planned03

Branches and Tags: Write-Audit-Publish, Experimentation, Retention Policies, Branch Writes, Tagging Releases, and Promotion Workflows: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter10/Lesson3.html

Planned04

Branches and Tags: Write-Audit-Publish, Experimentation, Retention Policies, Branch Writes, Tagging Releases, and Promotion Workflows: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter10/Lesson4.html

Planned05

Checkpoint Lab — Branches and Tags: Write-Audit-Publish, Experimentation, Retention Policies, Branch Writes, Tagging Releases, and Promotion Workflows: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter10/Lesson5.html

Planned

Chapter 11

Delete Semantics: Copy-on-Write vs Merge-on-Read Concepts, Equality Deletes, Position Deletes, and Reader/Writer Compatibility

5 lessons

Delete Semantics: Copy-on-Write vs Merge-on-Read Concepts, Equality Deletes, Position Deletes, and Reader/Writer Compatibility: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter11/Lesson1.html

Planned02

Delete Semantics: Copy-on-Write vs Merge-on-Read Concepts, Equality Deletes, Position Deletes, and Reader/Writer Compatibility: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter11/Lesson2.html

Planned03

Delete Semantics: Copy-on-Write vs Merge-on-Read Concepts, Equality Deletes, Position Deletes, and Reader/Writer Compatibility: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter11/Lesson3.html

Planned04

Delete Semantics: Copy-on-Write vs Merge-on-Read Concepts, Equality Deletes, Position Deletes, and Reader/Writer Compatibility: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter11/Lesson4.html

Planned05

Checkpoint Lab — Delete Semantics: Copy-on-Write vs Merge-on-Read Concepts, Equality Deletes, Position Deletes, and Reader/Writer Compatibility: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter11/Lesson5.html

Planned

Chapter 12

Deletion Vectors and Modern Row-Level Deletes: DV Semantics, Puffin-Backed Metadata, Reader Planning, Compaction Interactions, and Migration Considerations

5 lessons

Deletion Vectors and Modern Row-Level Deletes: DV Semantics, Puffin-Backed Metadata, Reader Planning, Compaction Interactions, and Migration Considerations: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter12/Lesson1.html

Planned02

Deletion Vectors and Modern Row-Level Deletes: DV Semantics, Puffin-Backed Metadata, Reader Planning, Compaction Interactions, and Migration Considerations: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter12/Lesson2.html

Planned03

Deletion Vectors and Modern Row-Level Deletes: DV Semantics, Puffin-Backed Metadata, Reader Planning, Compaction Interactions, and Migration Considerations: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter12/Lesson3.html

Planned04

Deletion Vectors and Modern Row-Level Deletes: DV Semantics, Puffin-Backed Metadata, Reader Planning, Compaction Interactions, and Migration Considerations: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter12/Lesson4.html

Planned05

Checkpoint Lab — Deletion Vectors and Modern Row-Level Deletes: DV Semantics, Puffin-Backed Metadata, Reader Planning, Compaction Interactions, and Migration Considerations: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter12/Lesson5.html

Planned

Chapter 13

Row Lineage and Row IDs: Row Identity, First Row IDs, Sequence Semantics, Change Tracking Foundations, and Format-Version Implications

5 lessons

Row Lineage and Row IDs: Row Identity, First Row IDs, Sequence Semantics, Change Tracking Foundations, and Format-Version Implications: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter13/Lesson1.html

Planned02

Row Lineage and Row IDs: Row Identity, First Row IDs, Sequence Semantics, Change Tracking Foundations, and Format-Version Implications: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter13/Lesson2.html

Planned03

Row Lineage and Row IDs: Row Identity, First Row IDs, Sequence Semantics, Change Tracking Foundations, and Format-Version Implications: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter13/Lesson3.html

Planned04

Row Lineage and Row IDs: Row Identity, First Row IDs, Sequence Semantics, Change Tracking Foundations, and Format-Version Implications: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter13/Lesson4.html

Planned05

Checkpoint Lab — Row Lineage and Row IDs: Row Identity, First Row IDs, Sequence Semantics, Change Tracking Foundations, and Format-Version Implications: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter13/Lesson5.html

Planned

Chapter 14

Format Versions 1, 2, and 3: Capability Boundaries, Upgrade Rules, Compatibility, Delete Evolution, Row Lineage, and Safe Version Adoption

5 lessons

Format Versions 1, 2, and 3: Capability Boundaries, Upgrade Rules, Compatibility, Delete Evolution, Row Lineage, and Safe Version Adoption: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter14/Lesson1.html

Planned02

Format Versions 1, 2, and 3: Capability Boundaries, Upgrade Rules, Compatibility, Delete Evolution, Row Lineage, and Safe Version Adoption: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter14/Lesson2.html

Planned03

Format Versions 1, 2, and 3: Capability Boundaries, Upgrade Rules, Compatibility, Delete Evolution, Row Lineage, and Safe Version Adoption: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter14/Lesson3.html

Planned04

Format Versions 1, 2, and 3: Capability Boundaries, Upgrade Rules, Compatibility, Delete Evolution, Row Lineage, and Safe Version Adoption: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter14/Lesson4.html

Planned05

Checkpoint Lab — Format Versions 1, 2, and 3: Capability Boundaries, Upgrade Rules, Compatibility, Delete Evolution, Row Lineage, and Safe Version Adoption: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter14/Lesson5.html

Planned

Chapter 15

File Formats and Metrics: Parquet/Avro/ORC Integration, Lower/Upper Bounds, Null/NaN Counts, Column Sizes, Split Offsets, and Statistics Quality

5 lessons

File Formats and Metrics: Parquet/Avro/ORC Integration, Lower/Upper Bounds, Null/NaN Counts, Column Sizes, Split Offsets, and Statistics Quality: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter15/Lesson1.html

Planned02

File Formats and Metrics: Parquet/Avro/ORC Integration, Lower/Upper Bounds, Null/NaN Counts, Column Sizes, Split Offsets, and Statistics Quality: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter15/Lesson2.html

Planned03

File Formats and Metrics: Parquet/Avro/ORC Integration, Lower/Upper Bounds, Null/NaN Counts, Column Sizes, Split Offsets, and Statistics Quality: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter15/Lesson3.html

Planned04

File Formats and Metrics: Parquet/Avro/ORC Integration, Lower/Upper Bounds, Null/NaN Counts, Column Sizes, Split Offsets, and Statistics Quality: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter15/Lesson4.html

Planned05

Checkpoint Lab — File Formats and Metrics: Parquet/Avro/ORC Integration, Lower/Upper Bounds, Null/NaN Counts, Column Sizes, Split Offsets, and Statistics Quality: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter15/Lesson5.html

Planned

Chapter 16

Scan Planning and Pruning: Manifest Pruning, Partition Pruning, Metrics Filtering, Residuals, Split Planning, and Metadata/Driver Pressure

5 lessons

Scan Planning and Pruning: Manifest Pruning, Partition Pruning, Metrics Filtering, Residuals, Split Planning, and Metadata/Driver Pressure: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter16/Lesson1.html

Planned02

Scan Planning and Pruning: Manifest Pruning, Partition Pruning, Metrics Filtering, Residuals, Split Planning, and Metadata/Driver Pressure: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter16/Lesson2.html

Planned03

Scan Planning and Pruning: Manifest Pruning, Partition Pruning, Metrics Filtering, Residuals, Split Planning, and Metadata/Driver Pressure: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter16/Lesson3.html

Planned04

Scan Planning and Pruning: Manifest Pruning, Partition Pruning, Metrics Filtering, Residuals, Split Planning, and Metadata/Driver Pressure: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter16/Lesson4.html

Planned05

Checkpoint Lab — Scan Planning and Pruning: Manifest Pruning, Partition Pruning, Metrics Filtering, Residuals, Split Planning, and Metadata/Driver Pressure: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter16/Lesson5.html

Planned

Chapter 17

Catalogs: Hadoop/Hive/JDBC/REST/Glue/Nessie-Style Concepts, Namespaces, Table Registration, Catalog Selection, and Portability Boundaries

5 lessons

Catalogs: Hadoop/Hive/JDBC/REST/Glue/Nessie-Style Concepts, Namespaces, Table Registration, Catalog Selection, and Portability Boundaries: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter17/Lesson1.html

Planned02

Catalogs: Hadoop/Hive/JDBC/REST/Glue/Nessie-Style Concepts, Namespaces, Table Registration, Catalog Selection, and Portability Boundaries: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter17/Lesson2.html

Planned03

Catalogs: Hadoop/Hive/JDBC/REST/Glue/Nessie-Style Concepts, Namespaces, Table Registration, Catalog Selection, and Portability Boundaries: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter17/Lesson3.html

Planned04

Catalogs: Hadoop/Hive/JDBC/REST/Glue/Nessie-Style Concepts, Namespaces, Table Registration, Catalog Selection, and Portability Boundaries: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter17/Lesson4.html

Planned05

Checkpoint Lab — Catalogs: Hadoop/Hive/JDBC/REST/Glue/Nessie-Style Concepts, Namespaces, Table Registration, Catalog Selection, and Portability Boundaries: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter17/Lesson5.html

Planned

Chapter 18

REST Catalog Deep Dive: Protocol, Authentication, Namespaces, Transactions, Server-Side Scan Planning, Remote Planning, and Multi-Engine Control Planes

5 lessons

REST Catalog Deep Dive: Protocol, Authentication, Namespaces, Transactions, Server-Side Scan Planning, Remote Planning, and Multi-Engine Control Planes: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter18/Lesson1.html

Planned02

REST Catalog Deep Dive: Protocol, Authentication, Namespaces, Transactions, Server-Side Scan Planning, Remote Planning, and Multi-Engine Control Planes: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter18/Lesson2.html

Planned03

REST Catalog Deep Dive: Protocol, Authentication, Namespaces, Transactions, Server-Side Scan Planning, Remote Planning, and Multi-Engine Control Planes: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter18/Lesson3.html

Planned04

REST Catalog Deep Dive: Protocol, Authentication, Namespaces, Transactions, Server-Side Scan Planning, Remote Planning, and Multi-Engine Control Planes: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter18/Lesson4.html

Planned05

Checkpoint Lab — REST Catalog Deep Dive: Protocol, Authentication, Namespaces, Transactions, Server-Side Scan Planning, Remote Planning, and Multi-Engine Control Planes: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter18/Lesson5.html

Planned

Chapter 19

Spark Integration: Catalog Configuration, DDL/DML, MERGE/UPDATE/DELETE, DataFrame Writes, Procedures, Extensions, and Maintenance

5 lessons

Spark Integration: Catalog Configuration, DDL/DML, MERGE/UPDATE/DELETE, DataFrame Writes, Procedures, Extensions, and Maintenance: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter19/Lesson1.html

Planned02

Spark Integration: Catalog Configuration, DDL/DML, MERGE/UPDATE/DELETE, DataFrame Writes, Procedures, Extensions, and Maintenance: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter19/Lesson2.html

Planned03

Spark Integration: Catalog Configuration, DDL/DML, MERGE/UPDATE/DELETE, DataFrame Writes, Procedures, Extensions, and Maintenance: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter19/Lesson3.html

Planned04

Spark Integration: Catalog Configuration, DDL/DML, MERGE/UPDATE/DELETE, DataFrame Writes, Procedures, Extensions, and Maintenance: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter19/Lesson4.html

Planned05

Checkpoint Lab — Spark Integration: Catalog Configuration, DDL/DML, MERGE/UPDATE/DELETE, DataFrame Writes, Procedures, Extensions, and Maintenance: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter19/Lesson5.html

Planned

Chapter 20

Flink Integration: Catalogs, Streaming Reads/Writes, Upserts, Checkpoints, Distribution, Maintenance, and Stateful Pipeline Considerations

5 lessons

Flink Integration: Catalogs, Streaming Reads/Writes, Upserts, Checkpoints, Distribution, Maintenance, and Stateful Pipeline Considerations: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter20/Lesson1.html

Planned02

Flink Integration: Catalogs, Streaming Reads/Writes, Upserts, Checkpoints, Distribution, Maintenance, and Stateful Pipeline Considerations: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter20/Lesson2.html

Planned03

Flink Integration: Catalogs, Streaming Reads/Writes, Upserts, Checkpoints, Distribution, Maintenance, and Stateful Pipeline Considerations: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter20/Lesson3.html

Planned04

Flink Integration: Catalogs, Streaming Reads/Writes, Upserts, Checkpoints, Distribution, Maintenance, and Stateful Pipeline Considerations: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter20/Lesson4.html

Planned05

Checkpoint Lab — Flink Integration: Catalogs, Streaming Reads/Writes, Upserts, Checkpoints, Distribution, Maintenance, and Stateful Pipeline Considerations: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter20/Lesson5.html

Planned

Chapter 21

Trino and Federated SQL Integration: Catalog Properties, Metadata Caching, DML, Procedures, Predicate Pushdown, and Multi-Engine Concurrency

5 lessons

Trino and Federated SQL Integration: Catalog Properties, Metadata Caching, DML, Procedures, Predicate Pushdown, and Multi-Engine Concurrency: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter21/Lesson1.html

Planned02

Trino and Federated SQL Integration: Catalog Properties, Metadata Caching, DML, Procedures, Predicate Pushdown, and Multi-Engine Concurrency: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter21/Lesson2.html

Planned03

Trino and Federated SQL Integration: Catalog Properties, Metadata Caching, DML, Procedures, Predicate Pushdown, and Multi-Engine Concurrency: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter21/Lesson3.html

Planned04

Trino and Federated SQL Integration: Catalog Properties, Metadata Caching, DML, Procedures, Predicate Pushdown, and Multi-Engine Concurrency: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter21/Lesson4.html

Planned05

Checkpoint Lab — Trino and Federated SQL Integration: Catalog Properties, Metadata Caching, DML, Procedures, Predicate Pushdown, and Multi-Engine Concurrency: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter21/Lesson5.html

Planned

Chapter 22

PyIceberg and Language Ecosystem: Python Catalogs, Scans, Writes, Arrow Interop, Rust/Go/C++ Awareness, and Client Capability Matrices

5 lessons

PyIceberg and Language Ecosystem: Python Catalogs, Scans, Writes, Arrow Interop, Rust/Go/C++ Awareness, and Client Capability Matrices: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter22/Lesson1.html

Planned02

PyIceberg and Language Ecosystem: Python Catalogs, Scans, Writes, Arrow Interop, Rust/Go/C++ Awareness, and Client Capability Matrices: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter22/Lesson2.html

Planned03

PyIceberg and Language Ecosystem: Python Catalogs, Scans, Writes, Arrow Interop, Rust/Go/C++ Awareness, and Client Capability Matrices: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter22/Lesson3.html

Planned04

PyIceberg and Language Ecosystem: Python Catalogs, Scans, Writes, Arrow Interop, Rust/Go/C++ Awareness, and Client Capability Matrices: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter22/Lesson4.html

Planned05

Checkpoint Lab — PyIceberg and Language Ecosystem: Python Catalogs, Scans, Writes, Arrow Interop, Rust/Go/C++ Awareness, and Client Capability Matrices: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter22/Lesson5.html

Planned

Chapter 23

Object Storage Semantics: S3/GCS/Azure Concepts, Atomicity Assumptions, FileIO, Multipart Uploads, Credentials, Consistency, and Orphaned Objects

5 lessons

Object Storage Semantics: S3/GCS/Azure Concepts, Atomicity Assumptions, FileIO, Multipart Uploads, Credentials, Consistency, and Orphaned Objects: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter23/Lesson1.html

Planned02

Object Storage Semantics: S3/GCS/Azure Concepts, Atomicity Assumptions, FileIO, Multipart Uploads, Credentials, Consistency, and Orphaned Objects: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter23/Lesson2.html

Planned03

Object Storage Semantics: S3/GCS/Azure Concepts, Atomicity Assumptions, FileIO, Multipart Uploads, Credentials, Consistency, and Orphaned Objects: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter23/Lesson3.html

Planned04

Object Storage Semantics: S3/GCS/Azure Concepts, Atomicity Assumptions, FileIO, Multipart Uploads, Credentials, Consistency, and Orphaned Objects: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter23/Lesson4.html

Planned05

Checkpoint Lab — Object Storage Semantics: S3/GCS/Azure Concepts, Atomicity Assumptions, FileIO, Multipart Uploads, Credentials, Consistency, and Orphaned Objects: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter23/Lesson5.html

Planned

Chapter 24

Table Maintenance I: Expire Snapshots, Remove Orphan Files, Manifest Rewrites, Retention, Safety Windows, and Auditability

5 lessons

Table Maintenance I: Expire Snapshots, Remove Orphan Files, Manifest Rewrites, Retention, Safety Windows, and Auditability: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter24/Lesson1.html

Planned02

Table Maintenance I: Expire Snapshots, Remove Orphan Files, Manifest Rewrites, Retention, Safety Windows, and Auditability: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter24/Lesson2.html

Planned03

Table Maintenance I: Expire Snapshots, Remove Orphan Files, Manifest Rewrites, Retention, Safety Windows, and Auditability: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter24/Lesson3.html

Planned04

Table Maintenance I: Expire Snapshots, Remove Orphan Files, Manifest Rewrites, Retention, Safety Windows, and Auditability: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter24/Lesson4.html

Planned05

Checkpoint Lab — Table Maintenance I: Expire Snapshots, Remove Orphan Files, Manifest Rewrites, Retention, Safety Windows, and Auditability: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter24/Lesson5.html

Planned

Chapter 25

Table Maintenance II: Data Compaction, Delete-File Compaction, Bin Packing, Sort/Z-Order-Like Strategies, Scheduling, and Cost Control

5 lessons

Table Maintenance II: Data Compaction, Delete-File Compaction, Bin Packing, Sort/Z-Order-Like Strategies, Scheduling, and Cost Control: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter25/Lesson1.html

Planned02

Table Maintenance II: Data Compaction, Delete-File Compaction, Bin Packing, Sort/Z-Order-Like Strategies, Scheduling, and Cost Control: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter25/Lesson2.html

Planned03

Table Maintenance II: Data Compaction, Delete-File Compaction, Bin Packing, Sort/Z-Order-Like Strategies, Scheduling, and Cost Control: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter25/Lesson3.html

Planned04

Table Maintenance II: Data Compaction, Delete-File Compaction, Bin Packing, Sort/Z-Order-Like Strategies, Scheduling, and Cost Control: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter25/Lesson4.html

Planned05

Checkpoint Lab — Table Maintenance II: Data Compaction, Delete-File Compaction, Bin Packing, Sort/Z-Order-Like Strategies, Scheduling, and Cost Control: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter25/Lesson5.html

Planned

Chapter 26

Performance Engineering: File Sizing, Partition Cardinality, Manifest Growth, Delete Density, Planning Latency, Parallelism, and Benchmark Design

5 lessons

Performance Engineering: File Sizing, Partition Cardinality, Manifest Growth, Delete Density, Planning Latency, Parallelism, and Benchmark Design: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter26/Lesson1.html

Planned02

Performance Engineering: File Sizing, Partition Cardinality, Manifest Growth, Delete Density, Planning Latency, Parallelism, and Benchmark Design: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter26/Lesson2.html

Planned03

Performance Engineering: File Sizing, Partition Cardinality, Manifest Growth, Delete Density, Planning Latency, Parallelism, and Benchmark Design: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter26/Lesson3.html

Planned04

Performance Engineering: File Sizing, Partition Cardinality, Manifest Growth, Delete Density, Planning Latency, Parallelism, and Benchmark Design: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter26/Lesson4.html

Planned05

Checkpoint Lab — Performance Engineering: File Sizing, Partition Cardinality, Manifest Growth, Delete Density, Planning Latency, Parallelism, and Benchmark Design: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter26/Lesson5.html

Planned

Chapter 27

Streaming and CDC Patterns: Incremental Appends, Changelog Semantics, Upserts through Engines, Watermarks, Exactly-Once Boundaries, and Reprocessing

5 lessons

Streaming and CDC Patterns: Incremental Appends, Changelog Semantics, Upserts through Engines, Watermarks, Exactly-Once Boundaries, and Reprocessing: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter27/Lesson1.html

Planned02

Streaming and CDC Patterns: Incremental Appends, Changelog Semantics, Upserts through Engines, Watermarks, Exactly-Once Boundaries, and Reprocessing: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter27/Lesson2.html

Planned03

Streaming and CDC Patterns: Incremental Appends, Changelog Semantics, Upserts through Engines, Watermarks, Exactly-Once Boundaries, and Reprocessing: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter27/Lesson3.html

Planned04

Streaming and CDC Patterns: Incremental Appends, Changelog Semantics, Upserts through Engines, Watermarks, Exactly-Once Boundaries, and Reprocessing: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter27/Lesson4.html

Planned05

Checkpoint Lab — Streaming and CDC Patterns: Incremental Appends, Changelog Semantics, Upserts through Engines, Watermarks, Exactly-Once Boundaries, and Reprocessing: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter27/Lesson5.html

Planned

Chapter 28

Security and Governance: Catalog Authorization, Object-Store IAM, Encryption, Credential Vending, Row/Column Policy Integration, Audit, and Least Privilege

5 lessons

Security and Governance: Catalog Authorization, Object-Store IAM, Encryption, Credential Vending, Row/Column Policy Integration, Audit, and Least Privilege: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter28/Lesson1.html

Planned02

Security and Governance: Catalog Authorization, Object-Store IAM, Encryption, Credential Vending, Row/Column Policy Integration, Audit, and Least Privilege: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter28/Lesson2.html

Planned03

Security and Governance: Catalog Authorization, Object-Store IAM, Encryption, Credential Vending, Row/Column Policy Integration, Audit, and Least Privilege: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter28/Lesson3.html

Planned04

Security and Governance: Catalog Authorization, Object-Store IAM, Encryption, Credential Vending, Row/Column Policy Integration, Audit, and Least Privilege: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter28/Lesson4.html

Planned05

Checkpoint Lab — Security and Governance: Catalog Authorization, Object-Store IAM, Encryption, Credential Vending, Row/Column Policy Integration, Audit, and Least Privilege: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter28/Lesson5.html

Planned

Chapter 29

Observability and Troubleshooting: Metadata Inspection, Snapshot Graphs, Manifest Counts, Commit Failures, Corrupt References, Slow Planning, and File-Level Diagnostics

5 lessons

Observability and Troubleshooting: Metadata Inspection, Snapshot Graphs, Manifest Counts, Commit Failures, Corrupt References, Slow Planning, and File-Level Diagnostics: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter29/Lesson1.html

Planned02

Observability and Troubleshooting: Metadata Inspection, Snapshot Graphs, Manifest Counts, Commit Failures, Corrupt References, Slow Planning, and File-Level Diagnostics: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter29/Lesson2.html

Planned03

Observability and Troubleshooting: Metadata Inspection, Snapshot Graphs, Manifest Counts, Commit Failures, Corrupt References, Slow Planning, and File-Level Diagnostics: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter29/Lesson3.html

Planned04

Observability and Troubleshooting: Metadata Inspection, Snapshot Graphs, Manifest Counts, Commit Failures, Corrupt References, Slow Planning, and File-Level Diagnostics: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter29/Lesson4.html

Planned05

Checkpoint Lab — Observability and Troubleshooting: Metadata Inspection, Snapshot Graphs, Manifest Counts, Commit Failures, Corrupt References, Slow Planning, and File-Level Diagnostics: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter29/Lesson5.html

Planned

Chapter 30

Migration and Interoperability: Converting Existing Tables, Registering Metadata, Multi-Format Coexistence, XTable-Style Translation Awareness, and Rollback Strategy

5 lessons

Migration and Interoperability: Converting Existing Tables, Registering Metadata, Multi-Format Coexistence, XTable-Style Translation Awareness, and Rollback Strategy: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter30/Lesson1.html

Planned02

Migration and Interoperability: Converting Existing Tables, Registering Metadata, Multi-Format Coexistence, XTable-Style Translation Awareness, and Rollback Strategy: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter30/Lesson2.html

Planned03

Migration and Interoperability: Converting Existing Tables, Registering Metadata, Multi-Format Coexistence, XTable-Style Translation Awareness, and Rollback Strategy: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter30/Lesson3.html

Planned04

Migration and Interoperability: Converting Existing Tables, Registering Metadata, Multi-Format Coexistence, XTable-Style Translation Awareness, and Rollback Strategy: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter30/Lesson4.html

Planned05

Checkpoint Lab — Migration and Interoperability: Converting Existing Tables, Registering Metadata, Multi-Format Coexistence, XTable-Style Translation Awareness, and Rollback Strategy: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter30/Lesson5.html

Planned

Chapter 31

High Availability, Backup, and Disaster Recovery: Catalog HA, Metadata Backups, Object Versioning, Region Failure, Restore Validation, and Recovery Drills

5 lessons

High Availability, Backup, and Disaster Recovery: Catalog HA, Metadata Backups, Object Versioning, Region Failure, Restore Validation, and Recovery Drills: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter31/Lesson1.html

Planned02

High Availability, Backup, and Disaster Recovery: Catalog HA, Metadata Backups, Object Versioning, Region Failure, Restore Validation, and Recovery Drills: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter31/Lesson2.html

Planned03

High Availability, Backup, and Disaster Recovery: Catalog HA, Metadata Backups, Object Versioning, Region Failure, Restore Validation, and Recovery Drills: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter31/Lesson3.html

Planned04

High Availability, Backup, and Disaster Recovery: Catalog HA, Metadata Backups, Object Versioning, Region Failure, Restore Validation, and Recovery Drills: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter31/Lesson4.html

Planned05

Checkpoint Lab — High Availability, Backup, and Disaster Recovery: Catalog HA, Metadata Backups, Object Versioning, Region Failure, Restore Validation, and Recovery Drills: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter31/Lesson5.html

Planned

Chapter 32

Production Capstone: Design, Ingest, Evolve, Branch, Mutate, Compact, Secure, Observe, Fail, Recover, and Benchmark an Iceberg 1.11 Lakehouse

5 lessons

Production Capstone: Design, Ingest, Evolve, Branch, Mutate, Compact, Secure, Observe, Fail, Recover, and Benchmark an Iceberg 1.11 Lakehouse: Concepts, Terminology, Architecture, and Mental ModelPlanned lesson · reserved path Chapter32/Lesson1.html

Planned02

Production Capstone: Design, Ingest, Evolve, Branch, Mutate, Compact, Secure, Observe, Fail, Recover, and Benchmark an Iceberg 1.11 Lakehouse: Guided Hands-On Workflow, Commands, APIs, and ConfigurationPlanned lesson · reserved path Chapter32/Lesson2.html

Planned03

Production Capstone: Design, Ingest, Evolve, Branch, Mutate, Compact, Secure, Observe, Fail, Recover, and Benchmark an Iceberg 1.11 Lakehouse: Design Choices, Scaling Behavior, Compatibility, and TradeoffsPlanned lesson · reserved path Chapter32/Lesson3.html

Planned04

Production Capstone: Design, Ingest, Evolve, Branch, Mutate, Compact, Secure, Observe, Fail, Recover, and Benchmark an Iceberg 1.11 Lakehouse: Failure Modes, Diagnostics, Security, Reliability, and PerformancePlanned lesson · reserved path Chapter32/Lesson4.html

Planned05

Checkpoint Lab — Production Capstone: Design, Ingest, Evolve, Branch, Mutate, Compact, Secure, Observe, Fail, Recover, and Benchmark an Iceberg 1.11 Lakehouse: Build, Test, Measure, Troubleshoot, and Explain the ResultPlanned lesson · reserved path Chapter32/Lesson5.html

Planned