Durga Analytics/ClickHouse - Developer Track

  • $999

ClickHouse - Developer Track

  • Course
  • 114 Lessons

SQL & Table Engines Materialized Views Joins, Aggregations & Window Functions

Contents

Module 3 — Advanced SQL Queries (Chapters 41–80)

Module 3 — Advanced SQL Queries.pdf
03_CLICKHOUSE-ARCHITECTURE_ADVANCED_SQL_PART1_Durga.mp4
03_CLICKHOUSE-ARCHITECTURE_ADVANCED_SQL_PART2_Durga.mp4
03_CLICKHOUSE-ARCHITECTURE_ADVANCED_SQL_PART3_Durga.mp4
59 Query profiling.m4a
77 Dashboard query design.m4a
73 Query performance tuning.m4a
44 Window functions.m4a
46 Nested queries.m4a
54 Distributed joins.m4a
74 Billion-row query optimization.m4a
53 JOIN optimization.m4a
56 Approximate functions.m4a
64 Time-series queries.m4a
76 Analytical workloads.m4a
51 Conditional expressions.m4a
75 Query anti-patterns.m4a
65 Event analytics queries.m4a
62 Handling large datasets.m4a
69 Query concurrency.m4a
41 SQL syntax deep dive.m4a
57 Statistical functions.m4a
49 JSON data processing.m4a
48 Map data types.m4a
61 Query optimization strategies.m4a
43 Aggregate functions.m4a
60 Execution plan analysis.m4a
63 Analytical query patterns.m4a
68 Query debugging.m4a
45 Subqueries.m4a
79 SQL performance case studies.m4a
80 SQL mastery review.m4a
67 Projections.m4a
71 Advanced aggregations.m4a
47 Array functions.m4a
72 Complex analytics queries.m4a
52 JOIN types.m4a
58 Geo functions.m4a
50 Date and time functions.m4a
78 Real-time query pipelines.m4a
42 Filtering and projections.m4a
70 Resource management.m4a
55 Aggregation optimization.m4a
66 Query caching.m4a

Module 4 — Table Engines & Storage Design (Chapters 81–110)

04_CLICKHOUSE_TABLE-ENGINES_STORAGE-DESIGN_PART1_Durga.mp4
04_CLICKHOUSE_TABLE-ENGINES_STORAGE-DESIGN_PART2_Durga.mp4
04_CLICKHOUSE_TABLE-ENGINES_STORAGE-DESIGN_PART3_Durga.mp4
Module 4 — Table Engines & Storage Design.pdf
89 Memory engine.m4a
82 MergeTree engine.m4a
86 CollapsingMergeTree.m4a
87 VersionedCollapsingMergeTree.m4a
92 Choosing the right engine.m4a
96 Deduplication strategies.m4a
88 Log engines.m4a
103 Wide tables vs star schema.m4a
98 TTL configuration.m4a
95 High-cardinality handling.m4a
104 Fact tables.m4a
100 Compression tuning.m4a
105 Dimension tables.m4a
102 Analytical schema design.m4a
110 Storage design review.m4a
85 AggregatingMergeTree.m4a
83 ReplacingMergeTree.m4a
90 Distributed engine.m4a
93 Partition design strategies.m4a
106 Incremental aggregation tables.m4a
107 Streaming event tables.m4a
84 SummingMergeTree.m4a
97 Data retention policies.m4a
81 Table engine overview.m4a
99 Storage optimization.m4a
108 Time-series schemas.m4a
91 Engine comparison.m4a
109 Schema anti-patterns.m4a
94 Sorting key optimization.m4a
101 Schema evolution.m4a

Module 5 — Materialized Views & Caching (Chapters 111–130)

Module 5 — Materialized Views & Caching.pdf
113 Incremental aggregation views.m4a
124 Analytics pipelines with views.m4a
126 Debugging materialized views.m4a
122 Real-time aggregation models.m4a
119 Projections vs views.m4a
127 View optimization.m4a
112 Creating materialized views.m4a
118 Refresh strategies.m4a
121 Query result caching.m4a
120 Aggregation caching.m4a
114 Pre-computation strategies.m4a
125 Handling late-arriving data.m4a
115 Materialized view pipelines.m4a
123 Streaming aggregations.m4a
128 Scaling view pipelines.m4a
116 Query acceleration with views.m4a
129 View architecture patterns.m4a
111 Materialized view fundamentals.m4a
117 Materialized view maintenance.m4a
130 Materialized view review.m4a
05_CLICKHOUSE_MATERIALIZED-VIEWS_CACHING_PART1_Durga.mp4
05_CLICKHOUSE_MATERIALIZED-VIEWS_CACHING_PART2_Durga.mp4

Module 11 — Performance Benchmark Lab (Chapters 281–290)

Module 11 — Performance Benchmark Lab.pdf
286 Compression benchmarking.m4a
289 Performance report creation.m4a
285 Partition tuning experiments.m4a
283 Query profiling exercises.m4a
290 Benchmark lab review.m4a
282 Loading billion-row datasets.m4a
281 Benchmark dataset setup.m4a
284 Aggregation performance tests.m4a
287 Query optimization challenge.m4a
288 Benchmark analysis.m4a
11_CLICKHOUSE_PERFORMANCE-BENCHMARK_LAB_Durga.mp4
clickhouse-analytics-lab.zip