Bright Dataによる構造化された大量データ抽出のウェブスパイダー
上級
これはEngineering, Product分野の自動化ワークフローで、16個のノードを含みます。主にIf, Set, Wait, Function, Aggregateなどのノードを使用。 Bright DataとWebhookを使った非同期バッチWebスクレイピング
前提条件
- •ターゲットAPIの認証情報が必要な場合あり
ワークフロープレビュー
ノード接続関係を可視化、ズームとパンをサポート
ワークフローをエクスポート
以下のJSON設定をn8nにインポートして、このワークフローを使用できます
{
"id": "OjwmaLrXhW4pO5ph",
"meta": {
"instanceId": "885b4fb4a6a9c2cb5621429a7b972df0d05bb724c20ac7dac7171b62f1c7ef40"
},
"name": "Structured Bulk Data Extract with Bright Data Web Scraper",
"tags": [
{
"id": "Kujft2FOjmOVQAmJ",
"name": "Engineering",
"createdAt": "2025-04-09T01:31:00.558Z",
"updatedAt": "2025-04-09T01:31:00.558Z"
},
{
"id": "ZOwtAMLepQaGW76t",
"name": "Building Blocks",
"createdAt": "2025-04-13T15:23:40.462Z",
"updatedAt": "2025-04-13T15:23:40.462Z"
}
],
"nodes": [
{
"id": "1bdca5ae-1e56-4cf2-a8dc-e135a6a2dfec",
"name": "「テスト実行」クリック時",
"type": "n8n-nodes-base.manualTrigger",
"position": [
-900,
-395
],
"parameters": {},
"typeVersion": 1
},
{
"id": "533968cd-1329-4a86-8875-478600ed82b7",
"name": "If",
"type": "n8n-nodes-base.if",
"position": [
200,
-470
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "6a7e5360-4cb5-4806-892e-5c85037fa71c",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.status }}",
"rightValue": "ready"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "83991fdf-0402-4de3-bbb5-7050e3e9fb62",
"name": "Set Snapshot Id",
"type": "n8n-nodes-base.set",
"position": [
-240,
-395
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "2c3369c6-9206-45d7-9349-f577baeaf189",
"name": "snapshot_id",
"type": "string",
"value": "={{ $json.snapshot_id }}"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "408a36af-decb-49b3-a95e-a2df0b6eea5f",
"name": "Download Snapshot",
"type": "n8n-nodes-base.httpRequest",
"position": [
640,
-520
],
"parameters": {
"url": "=https://api.brightdata.com/datasets/v3/snapshot/{{ $json.snapshot_id }}",
"options": {
"timeout": 10000
},
"sendQuery": true,
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"queryParameters": {
"parameters": [
{
"name": "format",
"value": "json"
}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "kdbqXuxIR8qIxF7y",
"name": "Header Auth account"
}
},
"typeVersion": 4.2
},
{
"id": "9d6cd882-c287-46ca-bc1e-df6b995fc422",
"name": "Wait",
"type": "n8n-nodes-base.wait",
"position": [
420,
-295
],
"webhookId": "631cd5de-36b3-4264-88ae-45b30e2c2ccc",
"parameters": {
"amount": 30
},
"typeVersion": 1.1
},
{
"id": "c9cf847a-6399-4c93-a901-30f1c0e7408a",
"name": "エラー確認",
"type": "n8n-nodes-base.if",
"position": [
420,
-520
],
"parameters": {
"options": {},
"conditions": {
"options": {
"version": 2,
"leftValue": "",
"caseSensitive": true,
"typeValidation": "strict"
},
"combinator": "and",
"conditions": [
{
"id": "b267071c-7102-407b-a98d-f613bcb1a106",
"operator": {
"type": "string",
"operation": "equals"
},
"leftValue": "={{ $json.errors.toString() }}",
"rightValue": "0"
}
]
}
},
"typeVersion": 2.2
},
{
"id": "b648614e-c33e-4818-8348-e95df56928c7",
"name": "スナップショットステータス確認",
"type": "n8n-nodes-base.httpRequest",
"position": [
-20,
-395
],
"parameters": {
"url": "=https://api.brightdata.com/datasets/v3/progress/{{ $json.snapshot_id }}",
"options": {},
"sendHeaders": true,
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"headerParameters": {
"parameters": [
{}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "kdbqXuxIR8qIxF7y",
"name": "Header Auth account"
}
},
"typeVersion": 4.2
},
{
"id": "408a1584-666f-471e-bfcd-c4d857319688",
"name": "Webhook通知の開始",
"type": "n8n-nodes-base.httpRequest",
"position": [
1080,
-520
],
"parameters": {
"url": "https://webhook.site/daf9d591-a130-4010-b1d3-0c66f8fcf467",
"options": {},
"sendBody": true,
"bodyParameters": {
"parameters": [
{
"name": "response",
"value": "={{ $json.data[0] }}"
}
]
}
},
"typeVersion": 4.2
},
{
"id": "6548a794-a4fd-4050-b07d-bc7ca4517882",
"name": "JSONレスポンスの集計",
"type": "n8n-nodes-base.aggregate",
"position": [
860,
-520
],
"parameters": {
"options": {},
"aggregate": "aggregateAllItemData"
},
"typeVersion": 1
},
{
"id": "c84e195c-edd2-4f59-8986-516d116b7352",
"name": "Set Dataset Id, Request URL",
"type": "n8n-nodes-base.set",
"position": [
-680,
-400
],
"parameters": {
"options": {},
"assignments": {
"assignments": [
{
"id": "c16061c8-c829-4bd3-b335-e79c605665f2",
"name": "dataset_id",
"type": "string",
"value": "gd_l7q7dkf244hwjntr0"
},
{
"id": "a4594c55-e39e-4a9e-80d6-d39370001e20",
"name": "request",
"type": "string",
"value": "[{ \"url\": \"https://www.amazon.com/Quencher-FlowState-Stainless-Insulated-Smoothie/dp/B0CRMZHDG8\" }]"
}
]
}
},
"typeVersion": 3.4
},
{
"id": "ceae108e-ed78-40c5-8e58-7013591ccaad",
"name": "付箋",
"type": "n8n-nodes-base.stickyNote",
"position": [
-900,
-700
],
"parameters": {
"width": 520,
"height": 280,
"content": "## Note\n\nDeals with the Amazon web scraping by utilizing Bright Data Web Scraper Product.\n\n\n**Please make sure to set the Bright Data \n -> Dataset Id, Request URL and update the Webhook Notification URL**\n\nRefer \n- https://brightdata.com/products/web-scraper/ai\n- https://brightdata.com/products/web-scraper"
},
"typeVersion": 1
},
{
"id": "1f55cffa-abd9-437b-bc9d-3fe0d8b02454",
"name": "付箋1",
"type": "n8n-nodes-base.stickyNote",
"position": [
-120,
-600
],
"parameters": {
"color": 5,
"width": 720,
"height": 500,
"content": "## Wait until the Snapshot is ready"
},
"typeVersion": 1
},
{
"id": "d8ba0f62-80a9-4e66-b70c-086ee5992df6",
"name": "付箋2",
"type": "n8n-nodes-base.stickyNote",
"position": [
-900,
-220
],
"parameters": {
"color": 4,
"width": 660,
"content": "## Who can benefit?\nData analysts, scientists, engineers, and developers seeking efficient methods to collect and analyze web data for AI, ML, big data applications, and more will find Scraper APIs particularly beneficial."
},
"typeVersion": 1
},
{
"id": "7fdffafd-f256-4760-b001-a42b5198dbad",
"name": "Create a binary data",
"type": "n8n-nodes-base.function",
"position": [
1100,
-720
],
"parameters": {
"functionCode": "items[0].binary = {\n data: {\n data: new Buffer(JSON.stringify(items[0].json, null, 2)).toString('base64')\n }\n};\nreturn items;"
},
"typeVersion": 1
},
{
"id": "934ab31a-cfb9-4e97-8d86-92cd95dd219c",
"name": "Write the file to disk",
"type": "n8n-nodes-base.readWriteFile",
"position": [
1320,
-720
],
"parameters": {
"options": {},
"fileName": "d:\\bulk_data.json",
"operation": "write"
},
"typeVersion": 1
},
{
"id": "1130523a-b598-425e-acf1-417ae8699f66",
"name": "指定URLへのHTTPリクエスト",
"type": "n8n-nodes-base.httpRequest",
"position": [
-460,
-395
],
"parameters": {
"url": "https://api.brightdata.com/datasets/v3/trigger",
"method": "POST",
"options": {},
"jsonBody": "={{ $json.request }}",
"sendBody": true,
"sendQuery": true,
"sendHeaders": true,
"specifyBody": "json",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"queryParameters": {
"parameters": [
{
"name": "dataset_id",
"value": "={{ $json.dataset_id }}"
},
{
"name": "format",
"value": "json"
},
{
"name": "uncompressed_webhook",
"value": "true"
}
]
},
"headerParameters": {
"parameters": [
{}
]
}
},
"credentials": {
"httpHeaderAuth": {
"id": "kdbqXuxIR8qIxF7y",
"name": "Header Auth account"
}
},
"typeVersion": 4.2
}
],
"active": false,
"pinData": {},
"settings": {
"executionOrder": "v1"
},
"versionId": "8fb2eb85-ffd6-4632-9668-00f29bc91c34",
"connections": {
"533968cd-1329-4a86-8875-478600ed82b7": {
"main": [
[
{
"node": "c9cf847a-6399-4c93-a901-30f1c0e7408a",
"type": "main",
"index": 0
}
],
[
{
"node": "9d6cd882-c287-46ca-bc1e-df6b995fc422",
"type": "main",
"index": 0
}
]
]
},
"9d6cd882-c287-46ca-bc1e-df6b995fc422": {
"main": [
[
{
"node": "b648614e-c33e-4818-8348-e95df56928c7",
"type": "main",
"index": 0
}
]
]
},
"83991fdf-0402-4de3-bbb5-7050e3e9fb62": {
"main": [
[
{
"node": "b648614e-c33e-4818-8348-e95df56928c7",
"type": "main",
"index": 0
}
]
]
},
"408a36af-decb-49b3-a95e-a2df0b6eea5f": {
"main": [
[
{
"node": "6548a794-a4fd-4050-b07d-bc7ca4517882",
"type": "main",
"index": 0
}
]
]
},
"c9cf847a-6399-4c93-a901-30f1c0e7408a": {
"main": [
[
{
"node": "408a36af-decb-49b3-a95e-a2df0b6eea5f",
"type": "main",
"index": 0
}
]
]
},
"7fdffafd-f256-4760-b001-a42b5198dbad": {
"main": [
[
{
"node": "934ab31a-cfb9-4e97-8d86-92cd95dd219c",
"type": "main",
"index": 0
}
]
]
},
"b648614e-c33e-4818-8348-e95df56928c7": {
"main": [
[
{
"node": "533968cd-1329-4a86-8875-478600ed82b7",
"type": "main",
"index": 0
}
]
]
},
"6548a794-a4fd-4050-b07d-bc7ca4517882": {
"main": [
[
{
"node": "408a1584-666f-471e-bfcd-c4d857319688",
"type": "main",
"index": 0
},
{
"node": "7fdffafd-f256-4760-b001-a42b5198dbad",
"type": "main",
"index": 0
}
]
]
},
"c84e195c-edd2-4f59-8986-516d116b7352": {
"main": [
[
{
"node": "1130523a-b598-425e-acf1-417ae8699f66",
"type": "main",
"index": 0
}
]
]
},
"1130523a-b598-425e-acf1-417ae8699f66": {
"main": [
[
{
"node": "83991fdf-0402-4de3-bbb5-7050e3e9fb62",
"type": "main",
"index": 0
}
]
]
},
"1bdca5ae-1e56-4cf2-a8dc-e135a6a2dfec": {
"main": [
[
{
"node": "c84e195c-edd2-4f59-8986-516d116b7352",
"type": "main",
"index": 0
}
]
]
}
}
}よくある質問
このワークフローの使い方は？
上記のJSON設定コードをコピーし、n8nインスタンスで新しいワークフローを作成して「JSONからインポート」を選択、設定を貼り付けて認証情報を必要に応じて変更してください。
このワークフローはどんな場面に適していますか？
上級 - エンジニアリング, プロダクト
有料ですか？
このワークフローは完全無料です。ただし、ワークフローで使用するサードパーティサービス（OpenAI APIなど）は別途料金が発生する場合があります。
関連ワークフロー
APIアーキテクチャ抽出ツール
APIアーキテクチャ抽出器
If
Set
Code
+
If
Set
Code
88 ノードPolina Medvedieva
エンジニアリング
Bright Data を使用して Google Gemini で Etsy データをスクレイピングし自動化
Etsy データマイニングの自動化を実現：Bright Data によるスクレピング、Google Gemini
Set
Function
Split Out
+
Set
Function
Split Out
19 ノードRanjan Dailata
プロダクト
DNB企業検索と抽出：Bright DataとOpenAI 4o miniを使用
Bright Data そして OpenAI 4o mini に基づく DNB 社検索と抽出
Set
Function
Mcp Client
+
Set
Function
Mcp Client
18 ノードRanjan Dailata
プロダクト
Googleトレンドデータ抽出、Bright DataとGoogle Geminiを使用して要約生成
Bright DataとGoogle Geminiを利用したGoogleトレンドデータ抽出と要約生成
Set
Gmail
Function
+
Set
Gmail
Function
16 ノードRanjan Dailata
エンジニアリング
Bright Data MCPサーバーとGoogle Geminiを使ったLinkedInウェブスクレイピング
Bright Data MCPサーバーとGoogle Geminiを使用したLinkedInデータの抽出・変換
Set
Code
Merge
+
Set
Code
Merge
20 ノードRanjan Dailata
人工知能
Bright DataとGoogle Geminiを使用したGoogle Mapsビジネス情報スクレイピングとリードリッチ化
Bright DataとGoogle Geminiを利用したGoogle Maps企業情報スクレイピングとリードリッチ化ツール
Set
Code
Wait
+
Set
Code
Wait
29 ノードRanjan Dailata
リード獲得
