From 7b0f5ccfa1f173d5abf1867a7607fbf570381d24 Mon Sep 17 00:00:00 2001 From: Sean Rose <1994030+sean-rose@users.noreply.github.com> Date: Fri, 19 Sep 2025 09:03:58 -0700 Subject: [PATCH 1/2] fix(docs): Correct summary of scheduled queries option for live data. --- src/cookbooks/live_data.md | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/src/cookbooks/live_data.md b/src/cookbooks/live_data.md index 4fc67eb30..4081ac74c 100644 --- a/src/cookbooks/live_data.md +++ b/src/cookbooks/live_data.md @@ -4,13 +4,13 @@ Use cases, such as real-time monitoring, dashboards, or personalized user experi ## Options for working with Live Data -| Option | Recommended Use Case | Data Size/Complexity | Latency | Setup Complexity | -| -------------------------------------- | ------------------------------------------------------ | ---------------------------------------------------- | --------- | ---------------- | -| 1. Querying Live Tables Directly | Small datasets or infrequent, simple queries | Low | 10-30 min | Low | -| 2. Scheduled queries | Medium | Periodic updates (e.g., hourly/daily) for dashboards | Medium | 1h or more | Medium | -| 3. Using Materialized Views | Large datasets, complex queries with low-latency needs | Medium to High | 10-30 min | Medium to High | -| 4. Dataflow | Very low-latency streaming for large datasets | High | <10 min | High | -| 5. Cloud function with Pub/Sub trigger | Low-latency for smaller subsets of data | Medium | <10 min | Medium to High | +| Option | Recommended Use Case | Data Size/Complexity | Latency | Setup Complexity | +| -------------------------------------- | ------------------------------------------------------ | ---------------------------------------------------- | ---------- | ---------------- | +| 1. Querying Live Tables Directly | Small datasets or infrequent, simple queries | Low | 10-30 min | Low | +| 2. Scheduled queries | Periodic updates (e.g., hourly/daily) for dashboards | Medium | 1h or more | Medium | +| 3. Using Materialized Views | Large datasets, complex queries with low-latency needs | Medium to High | 10-30 min | Medium to High | +| 4. Dataflow | Very low-latency streaming for large datasets | High | <10 min | High | +| 5. Cloud function with Pub/Sub trigger | Low-latency for smaller subsets of data | Medium | <10 min | Medium to High | Live ping tables are the final destination for the telemetry ingestion pipeline. Incoming ping data is loaded into these tables approximately every 10 minutes, though a delay of up to 30 minutes is normal. Data in these tables is set to expire after 30 days. From ac4047cc0aba90fce19cc6ae0f9f565c06783e5a Mon Sep 17 00:00:00 2001 From: Sean Rose <1994030+sean-rose@users.noreply.github.com> Date: Fri, 19 Sep 2025 09:08:50 -0700 Subject: [PATCH 2/2] fix: Compact table. --- src/cookbooks/live_data.md | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/src/cookbooks/live_data.md b/src/cookbooks/live_data.md index 4081ac74c..b28debda3 100644 --- a/src/cookbooks/live_data.md +++ b/src/cookbooks/live_data.md @@ -4,13 +4,13 @@ Use cases, such as real-time monitoring, dashboards, or personalized user experi ## Options for working with Live Data -| Option | Recommended Use Case | Data Size/Complexity | Latency | Setup Complexity | -| -------------------------------------- | ------------------------------------------------------ | ---------------------------------------------------- | ---------- | ---------------- | -| 1. Querying Live Tables Directly | Small datasets or infrequent, simple queries | Low | 10-30 min | Low | -| 2. Scheduled queries | Periodic updates (e.g., hourly/daily) for dashboards | Medium | 1h or more | Medium | -| 3. Using Materialized Views | Large datasets, complex queries with low-latency needs | Medium to High | 10-30 min | Medium to High | -| 4. Dataflow | Very low-latency streaming for large datasets | High | <10 min | High | -| 5. Cloud function with Pub/Sub trigger | Low-latency for smaller subsets of data | Medium | <10 min | Medium to High | +| Option | Recommended Use Case | Data Size/Complexity | Latency | Setup Complexity | +| -------------------------------------- | ------------------------------------------------------ | -------------------- | ---------- | ---------------- | +| 1. Querying Live Tables Directly | Small datasets or infrequent, simple queries | Low | 10-30 min | Low | +| 2. Scheduled queries | Periodic updates (e.g., hourly/daily) for dashboards | Medium | 1h or more | Medium | +| 3. Using Materialized Views | Large datasets, complex queries with low-latency needs | Medium to High | 10-30 min | Medium to High | +| 4. Dataflow | Very low-latency streaming for large datasets | High | <10 min | High | +| 5. Cloud function with Pub/Sub trigger | Low-latency for smaller subsets of data | Medium | <10 min | Medium to High | Live ping tables are the final destination for the telemetry ingestion pipeline. Incoming ping data is loaded into these tables approximately every 10 minutes, though a delay of up to 30 minutes is normal. Data in these tables is set to expire after 30 days.