Hey everyone, In today’s blog we are going to discuss about Clustering, By the end of this blog you will be able to understand below questions
What is Clustering? How we can add this ? When we need to choose the clustering ?
Let’s understand first, What is Clustering ?
Snowflake clustering is a technique employed in Snowflake tables to group related rows together within the same micro-partition, thereby enhancing query performance for accessing these rows. By organizing the data in a clustered manner, Snowflake can avoid scanning unnecessary micro-partitions during query execution.
Snowflake maintains clustering metadata for the micro-partitions in a table, including:
- The total number of micro-partitions that comprise the table.
- The number of micro-partitions containing values that overlap with each other (in a specified subset of table columns).
- The depth of the overlapping micro-partitions.
When data is loaded into Snowflake, it is initially stored in a “load table.” The load table is a temporary table used for staging data before it’s loaded into the actual table. Once the data is staged in the load table, Snowflake automatically reorganizes it into micro-partitions based on the Snowflake clustering keys defined for the table.
We can add the clustering key either at the table creation time or we can alter the table and then add clustering key using below syntax.
How will you make sure if table is clusterd or not? Just run SHOW TABLES and scroll right , you will see one column “ Automatic_Clustering” . If it is ON then yes clustering is added.
Note SYSTEM$CLUSTERING_INFROMATION function return all statistics about the clustering on any table.
Clustering will incur additional cost, To track the cost we will use the automatic_clustering_history view.
Using a clustering key to co-locate similar rows in the same micro-partitions enables several benefits for very large tables, including:
- Improved scan efficiency in queries by skipping data that does not match filtering predicates.
- Better column compression than in tables with no clustering. This is especially true when other columns are strongly correlated with the columns that comprise the clustering key.
- After a key has been defined on a table, no additional administration is required, unless you chose to drop or modify the key. All future maintenance on the rows in the table (to ensure optimal clustering) is performed automatically by Snowflake.
1- If the table contains a large number of micro-partitions (meaning that the table contains multiple terabytes of data)
Clustering is particularly beneficial for larger tables. In smaller tables, the performance gains may not be as significant.
2- Tables that are frequently accessed and queried can benefit from clustering, as it improves overall query performance by reducing the time required for data retrieval.
3- If your queries involve frequent joins between tables, clustering can enhance performance by organizing data based on the columns used for joins. This reduces the need for extensive data scanning during join operations.
4- If you have specific fields that are often filtered on or grouped by in queries.
5-If you have time-series data and want to cluster it by date to improve query performance.
1-If you have a small dataset that is not frequently queried, clustering may not provide much benefit.
2- If you have a dataset with low cardinality (few distinct values), clustering may not be very effective.
3-If you have a dataset that is already partitioned in a way that supports efficient querying, clustering may not be necessary.
4-If a table experiences frequent DML operations, clustering may not be the best choice, as it increases its cost.
Some other important points about Clustering:
In general, if a column (or expression) has higher cardinality, then maintaining clustering on that column is more expensive.
The cost of clustering on a unique key might be more than the benefit of clustering on that key, especially if point lookups are not the primary use case for that table.
If you are defining a multi-column clustering key for a table, the order in which the columns are specified in the CLUSTER BY clause is important. As a general rule, Snowflake recommends ordering the columns from lowest cardinality to highest cardinality. Putting a higher cardinality column before a lower cardinality column will generally reduce the effectiveness of clustering on the latter column.
HAPPY LEARNING :)
