Queries in Snowflake: Getting Started with Performance Optimizations
Snowflake
| Intermediate
- 16 videos | 1h 51m 33s
- Includes Assessment
- Earns a Badge
Partitioning data based on a column is a common technique for performance query optimization in many database technologies. Snowflake is a highly-performant, big-data technology that uses its own form of data partitioning called micro-partitioning that stores data in columnar format. In this course, discover the advantages of Snowflake micro-partitions over regular, static partitioning. Next, examine how caching works in Snowflake. Finally, learn how to perform the clustering of Snowflake tables and how clustering helps the performance of filters, point-lookups, and range queries on the clustering key columns. Upon completion, you'll be able to leverage micro-partitioning in Snowflake, differentiate between retrieval optimization caching and local disk caching, and implement clustering with the correct clustering key.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this course
Outline micro-partitioning in snowflake
Recognize query results and local disk caching
Load data into tables
Use caching for retrieval optimization in snowflake
Disable caching in snowflake
Query data using the local disk cache
Recall how clustering works in snowflake -
Recall how the overlap depth of micro-partitions is computed
Outline the concepts of clustering in snowflake
Choose clustering keys and view the resources saved by clustering on different columns
Use clustering and recall its advantages
Run queries on clustered date to query performance
Suspend clustering on a table
Cluster with multiple columns and evaluate the resulting performance
Summarize the key concepts covered in this course
IN THIS COURSE
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1m 9s
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6m 56s
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3. Snowflake Caching8m 9s
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4. Loading Data into Tables10m 26s
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5. Using Caching in Snowflake9m 13s
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6. Disabling Caching7m 22s
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7. Querying Data Using the Local Disk Cache7m 43s
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8. How Clustering Works in Snowflake4m 39s
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9. Overlap Depth of Micro-partitions6m 6s
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10. Snowflake Clustering Concepts7m 15s
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11. Choosing Clustering Keys11m 57s
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12. Using Clustering7m 38s
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13. Running Queries on Clustered Data6m 23s
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14. Suspending Clustering5m 4s
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15. Clustering with Multiple Key Columns7m 6s
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16. Course Summary4m 28s
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