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    "excerpt": "\u8907\u6570\u306e BigQuery \u30d7\u30ed\u30b8\u30a7\u30af\u30c8\u3068\u30e6\u30fc\u30b6\u30fc\u304c\u5b58\u5728\u3057\u3066\u3044\u308b\u5834\u5408\u306f\u3001\u30ab\u30b9\u30bf\u30e0\u5272\u308a\u5f53\u3066\u3092\u8981\u6c42\u3059\u308b\u3053\u3068\u3067\u8cbb\u7528\u3092\u7ba1\u7406\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u5272\u308a\u5f53\u3066\u3067\u306f\u30011 \u65e5\u306b\u51e6\u7406\u3055\u308c\u308b\u30c7\u30fc\u30bf\u91cf\u306e\u4e0a\u9650\u3092\u6307\u5b9a\u3057\u307e\u3059\u3002",
    "fetchedAt": "2026-09-07T01:12:12.342Z"
  },
  {
    "id": "bigquery-docs-64",
    "tier": "claimed-docs",
    "url": "https://cloud.google.com/bigquery/docs/query-plan-explanation",
    "excerpt": "BigQuery includes diagnostic query plan and timing information. This is similar to the information provided by statements such as `EXPLAIN` in other database and analytical systems.",
    "fetchedAt": "2026-09-07T01:12:12.342Z"
  },
  {
    "id": "bigquery-docs-65",
    "tier": "claimed-docs",
    "url": "https://cloud.google.com/bigquery/docs/access-control",
    "excerpt": "BigQuery: Roles and permissions that apply to BigQuery resources such as datasets, tables, views, and routines.",
    "fetchedAt": "2026-09-07T01:12:12.342Z"
  },
  {
    "id": "bigquery-docs-66",
    "tier": "claimed-docs",
    "url": "https://cloud.google.com/gemini/docs/bigquery/overview",
    "excerpt": "\u60a8\u8fd8\u53ef\u4ee5\u4f7f\u7528\u81ea\u7136\u8bed\u8a00\u67e5\u8be2\u6765\u5f00\u59cb\u6570\u636e\u5206\u6790\u3002\u5982\u9700\u4e86\u89e3\u5982\u4f55\u751f\u6210\u3001\u8865\u5168\u548c\u603b\u7ed3\u4ee3\u7801",
    "fetchedAt": "2026-09-07T01:12:12.342Z"
  },
  {
    "id": "bigquery-comm-1",
    "tier": "community",
    "url": "https://hn.algolia.com/api/v1/items/39446789",
    "excerpt": "User ran a script on BigQuery for HTTP Archive data and was billed $14,000 with zero warning; complained about lack of customer support and that Google wouldn't remove the fee.",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-comm-2",
    "tier": "community",
    "url": "https://hn.algolia.com/api/v1/items/39446789",
    "excerpt": "BQ hides query cost behind abstracted 'TBs scanned' or 'slots' mechanism; if GCP returned query cost directly in API/console it would be much easier for users, but that's not in Google's interest.",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-comm-3",
    "tier": "community",
    "url": "https://hn.algolia.com/api/v1/items/39446789",
    "excerpt": "BigQuery provides a dry run option to estimate bytes/costs before running a query, and shows bytes-to-be-scanned in small text before you hit run, which can help avoid surprise charges.",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-comm-4",
    "tier": "community",
    "url": "https://hn.algolia.com/api/v1/items/39446789",
    "excerpt": "I've worked with much larger datasets on BQ (petabyte scale) and managed to not spend more than $1000 in an hour; BQ tells you how much data will be processed BEFORE running the query.",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-comm-5",
    "tier": "community",
    "url": "https://hn.algolia.com/api/v1/items/35387822",
    "excerpt": "BigQuery was the only Google Cloud service used at a previous job -- everything else was AWS.",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-comm-6",
    "tier": "community",
    "url": "https://hn.algolia.com/api/v1/items/35387822",
    "excerpt": "Athena was extremely slow, like two orders of magnitude slower than BigQuery for the same queries, and its UI/documentation/UX is nowhere near as good as BigQuery's.",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-comm-7",
    "tier": "community",
    "url": "https://hn.algolia.com/api/v1/items/35387822",
    "excerpt": "BigQuery is much, much better than Redshift, though both are worse than Snowflake.",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-comm-8",
    "tier": "community",
    "url": "https://hn.algolia.com/api/v1/items/35387822",
    "excerpt": "Athena lets you query S3 data like BQ external tables, but BQ is much faster; Athena will easily be more expensive on larger datasets since you pay $5/TB scanned.",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-comm-9",
    "tier": "community",
    "url": "https://hn.algolia.com/api/v1/items/35387822",
    "excerpt": "BigQuery announced pricing changes: annual flat rate going from 2.3c to 4.8c per slot hour, and on-demand pricing increasing 25% (from $5/TB to $6.25/TB).",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-comm-10",
    "tier": "community",
    "url": "https://hn.algolia.com/api/v1/items/35387822",
    "excerpt": "BigQuery has on-demand pricing metered by data read, plus reserved slot pricing metered by time; reserved slots offer a considerable discount when compute is used continuously.",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-comm-11",
    "tier": "community",
    "url": "https://hn.algolia.com/api/v1/items/35387822",
    "excerpt": "BigQuery is one of the tools I've been most impressed with in the last 20 years -- it just works so much faster than I assumed it would.",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-comm-12",
    "tier": "community",
    "url": "https://hn.algolia.com/api/v1/items/35387822",
    "excerpt": "With the pricing shift to compressed storage, storage-heavy customers may see costs go down while compute costs rise; net effect depends on usage pattern and compression ratio.",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-comm-13",
    "tier": "community",
    "url": "https://news.ycombinator.com/item?id=19632263",
    "excerpt": "Pricing question: if you share a Sheet backed by 10TB BigQuery data with 10 people who each refresh 100 times a day, would that be 10,000TB/day (~$50,000/day)? Asked for clarification on how refresh billing works.",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-comm-14",
    "tier": "community",
    "url": "https://news.ycombinator.com/item?id=19632263",
    "excerpt": "Last time I checked, it was still hard to get a Google CloudSQL DB into BigQuery, so it's surprising they did the Sheets integration first; we used a third-party tool to copy CloudSQL data into BigQuery instead.",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-comm-15",
    "tier": "community",
    "url": "https://news.ycombinator.com/item?id=42998904",
    "excerpt": "Review after a week of using BigQuery's new SQL pipe syntax: much more productive for data exploration/cleaning, unifies WHERE/HAVING/QUALIFY, great for dbt macros, but readers must track more internal state through steps.",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-comm-16",
    "tier": "community",
    "url": "https://news.ycombinator.com/item?id=42998904",
    "excerpt": "BigQuery has table-valued functions already, which can be used with pipes with a CALL clause.",
    "fetchedAt": "2026-09-07T00:26:57.079Z"
  },
  {
    "id": "bigquery-probe-1",
    "tier": "probe",
    "url": "https://cloud.google.com/llms.txt",
    "excerpt": "PROBE llms.txt: HTTP 404 at https://cloud.google.com/llms.txt",
    "fetchedAt": "2026-09-07T00:27:45.551Z"
  },
  {
    "id": "bigquery-probe-2",
    "tier": "probe",
    "url": "https://cloud.google.com/openapi.json",
    "excerpt": "PROBE openapi: all candidate paths 404 (https://cloud.google.com/openapi.json, https://cloud.google.com/swagger.json, https://cloud.google.com/api/openapi.json, https://cloud.google.com/.well-known/openapi.json)",
    "fetchedAt": "2026-09-07T00:27:45.551Z"
  },
  {
    "id": "bigquery-probe-3",
    "tier": "probe",
    "url": "https://github.com/googleapis/mcp-toolbox",
    "excerpt": "official MCP server documented at https://github.com/googleapis/mcp-toolbox",
    "fetchedAt": "2026-09-07T00:27:45.551Z"
  },
  {
    "id": "bigquery-probe-4",
    "tier": "probe",
    "url": "https://cloud.google.com/bigquery/docs/bq-command-line-tool",
    "excerpt": "official CLI documented at https://cloud.google.com/bigquery/docs/bq-command-line-tool",
    "fetchedAt": "2026-09-07T00:27:45.551Z"
  },
  {
    "id": "bigquery-probe-rt-1",
    "tier": "probe",
    "url": "https://cloud.google.com/bigquery/docs/reference/rest",
    "excerpt": "PROBE runtime (recorded 2026-09-06): the BigQuery v2 REST discovery document downloaded keylessly from bigquery.googleapis.com and parsed cleanly \u2014 id bigquery:v2, basePath /bigquery/v2/, resources datasets/jobs/models/projects/routines/rowAccessPolicies/tabledata/tables \u2014 a machine-readable, self-describing API surface.",
    "fetchedAt": "2026-09-07T00:33:24.000Z"
  },
  {
    "id": "bigquery-probe-rt-2",
    "tier": "probe",
    "url": "https://github.com/googleapis/mcp-toolbox",
    "excerpt": "PROBE runtime (recorded 2026-09-06): Google's official MCP Toolbox for Databases ran from npm \u2014 `npx -y @toolbox-sdk/server --version` printed toolbox version 1.10.0 keylessly; starting the prebuilt BigQuery toolset requires ADC credentials and a BIGQUERY_PROJECT (documented), so the live server handshake is credential-gated.",
    "fetchedAt": "2026-09-07T00:33:24.000Z"
  },
  {
    "id": "bigquery-supp-compliance",
    "tier": "claimed-docs",
    "url": "https://cloud.google.com/security/compliance",
    "excerpt": "Google Cloud compliance resource center lists BigQuery-covered attestations and certifications including ISO 9001:2015, ISO 22301:2019, ISO 50001:2018, SOC 1/2/3, HIPAA support, and sector/regional programs, with downloadable reports per certification.",
    "fetchedAt": "2026-09-07T01:42:38.000Z"
  }
]