Apply partitioning and change clustering for replicated data base to BQ with DataFusion

[Trand]

I replicate data from MySQL data base to BigQuery using DataFusion.

My original table in MySQL is not partitioned but I want it to be partitioned by a column when it is replicated to BQ.

Additionally BQ assigns a column for clustering by default on its own for PK column when I run replication job in DataFusion.

Questions:

- Is it possible at the very beginning of replication job in DataFusion (MySQL -> BQ) to set some tables to become partitioned by specific columns, while the rest of replicated table leave replicating as they are?
- And is it possible to change or set cluster columns on start of the replication process to BQ?

[ms4446 · Accepted solution]

Yes, it is possible to set specific tables to be partitioned by specific columns and to change or set cluster columns at the start of the replication process from MySQL to BigQuery using DataFusion. However, the process involves a few important considerations:

Partitioning Tables:

1. Define Partitioning Scheme: Identify the columns you want to use for partitioning in each table. This step is crucial for optimizing query performance in BigQuery.

2. DataFusion Configuration: In DataFusion, configure your replication job to handle partitioning. This is typically done through the pipeline setup interface rather than SQL statements. Specify the partitioning scheme for each table within this configuration.

3. Automatic Table Creation: DataFusion often automatically creates and manages the schema of the destination tables in BigQuery. Therefore, manually pre-creating partitioned tables in BigQuery might not be necessary unless you have specific schema customizations.

Clustering Columns:

1. Identify Clustering Columns: Determine which columns should be used for clustering in BigQuery. Clustering organizes data to improve the efficiency of certain types of queries.

2. DataFusion Configuration: As of the last update, direct specification of clustering columns in DataFusion was not a standard feature. Therefore, you might need to configure clustering as a post-replication step in BigQuery. This involves altering the table to specify the clustering columns.

General Considerations:

• Automation vs. Customization: While DataFusion provides a high degree of automation for data replication, advanced configurations like specific partitioning and clustering might require additional manual setup or adjustments post-replication.
• Up-to-Date Practices: Google Cloud services are frequently updated. It's recommended to consult the latest DataFusion and BigQuery documentation for current features and best practices.

By understanding these details, you can effectively manage the partitioning and clustering of your tables in BigQuery during the replication process using DataFusion, thereby optimizing your data organization and query performance.

[ms4446 · Accepted solution]

Yes, it is possible to set specific tables to be partitioned by specific columns and to change or set cluster columns at the start of the replication process from MySQL to BigQuery using DataFusion. However, the process involves a few important considerations:

Partitioning Tables:

1. Define Partitioning Scheme: Identify the columns you want to use for partitioning in each table. This step is crucial for optimizing query performance in BigQuery.

2. DataFusion Configuration: In DataFusion, configure your replication job to handle partitioning. This is typically done through the pipeline setup interface rather than SQL statements. Specify the partitioning scheme for each table within this configuration.

3. Automatic Table Creation: DataFusion often automatically creates and manages the schema of the destination tables in BigQuery. Therefore, manually pre-creating partitioned tables in BigQuery might not be necessary unless you have specific schema customizations.

Clustering Columns:

1. Identify Clustering Columns: Determine which columns should be used for clustering in BigQuery. Clustering organizes data to improve the efficiency of certain types of queries.

2. DataFusion Configuration: As of the last update, direct specification of clustering columns in DataFusion was not a standard feature. Therefore, you might need to configure clustering as a post-replication step in BigQuery. This involves altering the table to specify the clustering columns.

General Considerations:

• Automation vs. Customization: While DataFusion provides a high degree of automation for data replication, advanced configurations like specific partitioning and clustering might require additional manual setup or adjustments post-replication.
• Up-to-Date Practices: Google Cloud services are frequently updated. It's recommended to consult the latest DataFusion and BigQuery documentation for current features and best practices.

By understanding these details, you can effectively manage the partitioning and clustering of your tables in BigQuery during the replication process using DataFusion, thereby optimizing your data organization and query performance.

[Trand]

Thanks for your response!

> typically done through the pipeline setup interface rather than SQL statements.

Could u please share link with this documentation since I've read tones of BQ & DF documentations  and have found it neither in in documentation nor in interface.

[ms4446]

Let me clarify, while DataFusion is a powerful tool for data integration and ETL processes, it does not currently support direct configuration of partitioning and clustering for BigQuery tables through its pipeline setup interface.

To configure partitioning and clustering for your BigQuery tables, you would typically manage these settings directly in BigQuery. This can be done either before loading data into BigQuery or by altering the table configurations after the data is loaded. Here are the steps you can follow:

1. Configure in BigQuery:

   • Pre-Loading: If possible, configure the partitioning and clustering settings in BigQuery before you start the data replication process from MySQL.
   • Post-Loading: Alternatively, you can alter the table configurations in BigQuery after the data has been loaded. This involves using SQL statements in the BigQuery interface to add PARTITIONED BY and CLUSTER BY clauses.

2. DataFusion's Role:

   • DataFusion is used primarily for data replication and transformation. While it supports SQL transformations, these are generally used for data manipulation rather than for setting up table schemas in BigQuery.

3. Documentation and Support:

   • For detailed instructions and best practices, refer to the latest BigQuery documentation on partitioning and clustering. If the documentation does not provide clear guidance, consider reaching out to Google Cloud support or exploring community forums for additional insights.

Again, while DataFusion facilitates the data replication process, the specific configuration of partitioning and clustering for BigQuery tables is more effectively managed directly within BigQuery. DataFusion's SQL capabilities are focused on data transformation rather than schema configuration.

[Trand]

Thanks again for quite comprehensive answer!

So the last question if BQ supports partitioning of already existing tables that are replicated?

The only trick I've seen is to create new table, drop original table and then rename table with the new name to the original name. But these manipulations were described not in context of data replication.

[ms4446 · Accepted solution]

No, BigQuery does not directly support partitioning of existing tables that are replicated. The method you described, creating a new partitioned table, dropping the original table, and then renaming the new table to the original name, is the recommended approach for partitioning existing replicated tables.

This approach involves some downtime as the original table is dropped and the new partitioned table is created. To minimize downtime, you can create the new partitioned table with the same schema as the original table and then copy the data from the original table to the new table. Once the data is copied, you can drop the original table and rename the new table to the original name.

Here's a summary of the steps involved:

1. Create a new partitioned table with the same schema as the original table.
2. Copy the data from the original table to the new partitioned table.
3. Drop the original table.
4. Rename the new partitioned table to the original name.

This approach ensures that the replicated table is partitioned and that there is no data loss during the process.

[Trand]

We've tried this way, everything seems fine. Thanks