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Add sample 'orders-streaming-analytics' - #184

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NicolasRicheYopp:orders-streaming-analytics

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@NicolasRicheYopp NicolasRicheYopp commented Sep 16, 2026

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This demo implements a dual-path streaming architecture ingesting orders (TCP-H dataset) where each branch addresses a distinct analytical goal.

The left branch (Lakehouse Aggregates path) handles predictable, day-to-day reporting by precomputing cumulative aggregates, such as daily order totals, and saving them directly into Spanner aggregate tables only when relevant data changes.

The right branch (Direct Spanner path) continuously maintains the raw orders table to support ad-hoc queries not covered by precomputations. By leveraging Spanner Data Boost alongside its columnar engine, these ad-hoc queries run efficiently without impacting the primary Spanner instance, thereby eliminating the need to over-provision it.

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This demo implements a dual-path streaming architecture ingesting orders (TCP-H dataset) where each branch addresses a distinct analytical goal.

The left branch (Lakehouse Aggregates path) handles predictable, day-to-day reporting by precomputing cumulative aggregates, such as daily order totals, and saving them directly into Spanner aggregate tables only when relevant data changes.

The right branch (Direct Spanner path) continuously maintains the raw orders table to support ad-hoc queries not covered by precomputations. By leveraging Spanner Data Boost alongside its columnar engine, these ad-hoc queries run efficiently without impacting the primary Spanner instance, thereby eliminating the need to over-provision it.
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