You need to ad hoc-join user-specific data from Cloud Spanner and Cloud Bigtable; Spanner backups are exported to Cloud Storage. Do this as efficiently as possible. What should you do?
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Correct answer: Create BigQuery external tables over the Cloud Storage Spanner export and Cloud Bigtable, then join them in BigQuery with user filters..
Why this is the answer
Creating BigQuery external tables over the Cloud Storage Spanner export and Cloud Bigtable, then joining them in BigQuery with user filters, is the most efficient solution. BigQuery is optimized for large-scale ad hoc queries and joins, making it ideal for this scenario. External tables allow you to query data directly from Cloud Storage and Bigtable without ingesting it, saving time and resources. Dataflow is suitable for ETL pipelines but less efficient for ad hoc joins. Cloud Dataproc Spark jobs would involve managing a cluster, which is less efficient than BigQuery's serverless approach for this specific task.
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