Bigquery's performance may suffer when joining large tables, resulting in increased execution times and costs, especially as data volumes continue to grow.
To optimize JOINs in Bigquery, use strategies like partitioning by transaction_date and clustering by customer_id, which restricts data scanned during queries.
Pre-filtering data before executing a JOIN can significantly reduce the amount of data processed, improving query performance and lowering costs.
As datasets grow larger, the challenges of handling JOIN operations in Bigquery become more pronounced, leading to potential query failures and performance degradation.
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