In this video, discover the purpose of materialized views.
- [Instructor] Materialized views combine … some of the features of tables and views. … Materialized views are used to store … the results of pre-compute queries. … For example, we may have to perform an expensive join … and we want to minimize the number of times … we actually need to run that query. … By materializing or storing the results of the query, … we can use those stored results for other operations … without performing the expensive query again. … While materialized views can save time, … they will take up space. … Materialized views duplicate data … that is already stored in tables. … Data in materialized views can be stale. … You have to update or refresh materialized views … to capture changes to the source tables … that made up the materialized view. … Another thing to keep in mind … is that there is the potential for inconsistencies … between source tables and materialized views. … If you can tolerate these potential problems, … the materialized views may help you reduce …
Author
Released
4/1/2019- How SQL executes queries
- Working with PostgreSQL tools for tuning
- Bitmap and hash indexes
- Using different types of indexes to improve performance
- Challenges with joining tables
- When to use partitioning to improve performance
- Collecting statistics about data in tables
Skill Level Advanced
Duration
Views
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Introduction
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1. How SQL Executes a Query
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Scanning tables and indexes3m 12s
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Joining tables2m 24s
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Partitioning data2m 23s
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2. PostgreSQL Tools for Tuning
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Installing PostgreSQL2m 41s
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Overview of pgAdmin3m 21s
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Explain and analyze3m 37s
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Indexes3m 7s
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3. Types of Indexes
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Indexing3m 1s
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B-tree indexes2m 2s
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B-tree index example plan2m 18s
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Bitmap indexes1m 46s
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Bitmap index example plan2m 39s
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Hash indexes1m 19s
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Hash index example plan1m 32s
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PostgreSQL-specific indexes1m 17s
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4. Tuning Joins
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Nested loops3m 19s
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Nested loop example plan3m 55s
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Hash joins1m 25s
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Hash join example plan1m 57s
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Merge joins2m 17s
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Merge join example3m 16s
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Subqueries vs. joins1m 11s
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5. Partitioning Data
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Partition by range2m 6s
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Partition by list1m 37s
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Partition by list example4m 55s
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Partition by hash2m 12s
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Partition by hash example4m 51s
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6. Materialized Views
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Materialized views1m 41s
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7. Other Optimization Techniques
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Hints to the query optimizer2m 13s
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Parallel query execution2m 3s
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Miscellaneous tips1m 47s
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Conclusion
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Next steps41s
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Video: Materialized views