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108 lines
26 KiB
JSON
108 lines
26 KiB
JSON
{
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"data": {
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"question": {
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"questionId": "4043",
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"questionFrontendId": "3673",
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"categoryTitle": "Database",
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"boundTopicId": 3774328,
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"title": "Find Zombie Sessions",
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"titleSlug": "find-zombie-sessions",
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"content": "<p>Table: <code>app_events</code></p>\n\n<pre>\n+------------------+----------+\n| Column Name | Type | \n+------------------+----------+\n| event_id | int |\n| user_id | int |\n| event_timestamp | datetime |\n| event_type | varchar |\n| session_id | varchar |\n| event_value | int |\n+------------------+----------+\nevent_id is the unique identifier for this table.\nevent_type can be app_open, click, scroll, purchase, or app_close.\nsession_id groups events within the same user session.\nevent_value represents: for purchase - amount in dollars, for scroll - pixels scrolled, for others - NULL.\n</pre>\n\n<p>Write a solution to identify <strong>zombie sessions, </strong>sessions where users appear active but show abnormal behavior patterns. A session is considered a <strong>zombie session</strong> if it meets ALL the following criteria:</p>\n\n<ul>\n\t<li>The session duration is <strong>more than</strong> <code>30</code> minutes.</li>\n\t<li>Has <strong>at least</strong> <code>5</code> scroll events.</li>\n\t<li>The <strong>click-to-scroll ratio</strong> is less than <code>0.20</code> .</li>\n\t<li><strong>No purchases</strong> were made during the session.</li>\n</ul>\n\n<p>Return <em>the result table ordered by</em> <code>scroll_count</code> <em>in <strong>descending</strong> order, then by</em> <code>session_id</code> <em>in <strong>ascending</strong> order</em>.</p>\n\n<p>The result format is in the following example.</p>\n\n<p> </p>\n<p><strong class=\"example\">Example:</strong></p>\n\n<div class=\"example-block\">\n<p><strong>Input:</strong></p>\n\n<p>app_events table:</p>\n\n<pre class=\"example-io\">\n+----------+---------+---------------------+------------+------------+-------------+\n| event_id | user_id | event_timestamp | event_type | session_id | event_value |\n+----------+---------+---------------------+------------+------------+-------------+\n| 1 | 201 | 2024-03-01 10:00:00 | app_open | S001 | NULL |\n| 2 | 201 | 2024-03-01 10:05:00 | scroll | S001 | 500 |\n| 3 | 201 | 2024-03-01 10:10:00 | scroll | S001 | 750 |\n| 4 | 201 | 2024-03-01 10:15:00 | scroll | S001 | 600 |\n| 5 | 201 | 2024-03-01 10:20:00 | scroll | S001 | 800 |\n| 6 | 201 | 2024-03-01 10:25:00 | scroll | S001 | 550 |\n| 7 | 201 | 2024-03-01 10:30:00 | scroll | S001 | 900 |\n| 8 | 201 | 2024-03-01 10:35:00 | app_close | S001 | NULL |\n| 9 | 202 | 2024-03-01 11:00:00 | app_open | S002 | NULL |\n| 10 | 202 | 2024-03-01 11:02:00 | click | S002 | NULL |\n| 11 | 202 | 2024-03-01 11:05:00 | scroll | S002 | 400 |\n| 12 | 202 | 2024-03-01 11:08:00 | click | S002 | NULL |\n| 13 | 202 | 2024-03-01 11:10:00 | scroll | S002 | 350 |\n| 14 | 202 | 2024-03-01 11:15:00 | purchase | S002 | 50 |\n| 15 | 202 | 2024-03-01 11:20:00 | app_close | S002 | NULL |\n| 16 | 203 | 2024-03-01 12:00:00 | app_open | S003 | NULL |\n| 17 | 203 | 2024-03-01 12:10:00 | scroll | S003 | 1000 |\n| 18 | 203 | 2024-03-01 12:20:00 | scroll | S003 | 1200 |\n| 19 | 203 | 2024-03-01 12:25:00 | click | S003 | NULL |\n| 20 | 203 | 2024-03-01 12:30:00 | scroll | S003 | 800 |\n| 21 | 203 | 2024-03-01 12:40:00 | scroll | S003 | 900 |\n| 22 | 203 | 2024-03-01 12:50:00 | scroll | S003 | 1100 |\n| 23 | 203 | 2024-03-01 13:00:00 | app_close | S003 | NULL |\n| 24 | 204 | 2024-03-01 14:00:00 | app_open | S004 | NULL |\n| 25 | 204 | 2024-03-01 14:05:00 | scroll | S004 | 600 |\n| 26 | 204 | 2024-03-01 14:08:00 | scroll | S004 | 700 |\n| 27 | 204 | 2024-03-01 14:10:00 | click | S004 | NULL |\n| 28 | 204 | 2024-03-01 14:12:00 | app_close | S004 | NULL |\n+----------+---------+---------------------+------------+------------+-------------+\n</pre>\n\n<p><strong>Output:</strong></p>\n\n<pre class=\"example-io\">\n+------------+---------+--------------------------+--------------+\n| session_id | user_id | session_duration_minutes | scroll_count |\n+------------+---------+--------------------------+--------------+\n| S001 | 201 | 35 | 6 |\n+------------+---------+--------------------------+--------------+\n</pre>\n\n<p><strong>Explanation:</strong></p>\n\n<ul>\n\t<li><strong>Session S001 (User 201)</strong>:\n\n\t<ul>\n\t\t<li>Duration: 10:00:00 to 10:35:00 = 35 minutes (more than 30) </li>\n\t\t<li>Scroll events: 6 (at least 5) </li>\n\t\t<li>Click events: 0</li>\n\t\t<li>Click-to-scroll ratio: 0/6 = 0.00 (less than 0.20) </li>\n\t\t<li>Purchases: 0 (no purchases) </li>\n\t\t<li>S001 is a zombie session (meets all criteria)</li>\n\t</ul>\n\t</li>\n\t<li><strong>Session S002 (User 202)</strong>:\n\t<ul>\n\t\t<li>Duration: 11:00:00 to 11:20:00 = 20 minutes (less than 30) </li>\n\t\t<li>Has a purchase event </li>\n\t\t<li>S002 is not a zombie session </li>\n\t</ul>\n\t</li>\n\t<li><strong>Session S003 (User 203)</strong>:\n\t<ul>\n\t\t<li>Duration: 12:00:00 to 13:00:00 = 60 minutes (more than 30) </li>\n\t\t<li>Scroll events: 5 (at least 5) </li>\n\t\t<li>Click events: 1</li>\n\t\t<li>Click-to-scroll ratio: 1/5 = 0.20 (not less than 0.20) </li>\n\t\t<li>Purchases: 0 (no purchases) </li>\n\t\t<li>S003 is not a zombie session (click-to-scroll ratio equals 0.20, needs to be less)</li>\n\t</ul>\n\t</li>\n\t<li><strong>Session S004 (User 204)</strong>:\n\t<ul>\n\t\t<li>Duration: 14:00:00 to 14:12:00 = 12 minutes (less than 30) </li>\n\t\t<li>Scroll events: 2 (less than 5) </li>\n\t\t<li>S004 is not a zombie session </li>\n\t</ul>\n\t</li>\n</ul>\n\n<p>The result table is ordered by scroll_count in descending order, then by session_id in ascending order.</p>\n</div>\n",
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"translatedTitle": "查找僵尸会话",
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"translatedContent": "<p>表：<code>app_events</code></p>\n\n<pre>\n+------------------+----------+\n| Column Name | Type | \n+------------------+----------+\n| event_id | int |\n| user_id | int |\n| event_timestamp | datetime |\n| event_type | varchar |\n| session_id | varchar |\n| event_value | int |\n+------------------+----------+\nevent_id 是这张表的唯一主键。\nevent_type 可以是 app_open，click，scroll，purchase 或 app_close。\nsession_id 将事件按同一用户会话分组。\nevent_value 表示：对于 purchase - 美元金额，对于 scroll - 滚动的像素数，对于其它 - NULL。\n</pre>\n\n<p>编写一个解决方案来识别 <strong>僵尸会话</strong>，即用户看似活跃但表现出异常行为模式的会话。如果会话满足以下所有条件，则被视为 <strong>僵尸会话</strong>：</p>\n\n<ul>\n\t<li>会话时长 <strong>超过</strong> <code>30</code> 分钟。</li>\n\t<li>至少有 <code>5</code> 次滚动事件。</li>\n\t<li>点击滚动比率低于 <code>0.20</code>。</li>\n\t<li>会话期间 <strong>没有进行任何购买</strong>。</li>\n</ul>\n\n<p>返回结果表按 <code>scroll_count</code> <strong>降序</strong> 排序，然后按 <code>session_id</code> <strong>升序</strong> 排序。</p>\n\n<p>返回格式如下所示。</p>\n\n<p> </p>\n\n<p><strong class=\"example\">示例：</strong></p>\n\n<div class=\"example-block\">\n<p><strong>输入：</strong></p>\n\n<p>app_events 表：</p>\n\n<pre class=\"example-io\">\n+----------+---------+---------------------+------------+------------+-------------+\n| event_id | user_id | event_timestamp | event_type | session_id | event_value |\n+----------+---------+---------------------+------------+------------+-------------+\n| 1 | 201 | 2024-03-01 10:00:00 | app_open | S001 | NULL |\n| 2 | 201 | 2024-03-01 10:05:00 | scroll | S001 | 500 |\n| 3 | 201 | 2024-03-01 10:10:00 | scroll | S001 | 750 |\n| 4 | 201 | 2024-03-01 10:15:00 | scroll | S001 | 600 |\n| 5 | 201 | 2024-03-01 10:20:00 | scroll | S001 | 800 |\n| 6 | 201 | 2024-03-01 10:25:00 | scroll | S001 | 550 |\n| 7 | 201 | 2024-03-01 10:30:00 | scroll | S001 | 900 |\n| 8 | 201 | 2024-03-01 10:35:00 | app_close | S001 | NULL |\n| 9 | 202 | 2024-03-01 11:00:00 | app_open | S002 | NULL |\n| 10 | 202 | 2024-03-01 11:02:00 | click | S002 | NULL |\n| 11 | 202 | 2024-03-01 11:05:00 | scroll | S002 | 400 |\n| 12 | 202 | 2024-03-01 11:08:00 | click | S002 | NULL |\n| 13 | 202 | 2024-03-01 11:10:00 | scroll | S002 | 350 |\n| 14 | 202 | 2024-03-01 11:15:00 | purchase | S002 | 50 |\n| 15 | 202 | 2024-03-01 11:20:00 | app_close | S002 | NULL |\n| 16 | 203 | 2024-03-01 12:00:00 | app_open | S003 | NULL |\n| 17 | 203 | 2024-03-01 12:10:00 | scroll | S003 | 1000 |\n| 18 | 203 | 2024-03-01 12:20:00 | scroll | S003 | 1200 |\n| 19 | 203 | 2024-03-01 12:25:00 | click | S003 | NULL |\n| 20 | 203 | 2024-03-01 12:30:00 | scroll | S003 | 800 |\n| 21 | 203 | 2024-03-01 12:40:00 | scroll | S003 | 900 |\n| 22 | 203 | 2024-03-01 12:50:00 | scroll | S003 | 1100 |\n| 23 | 203 | 2024-03-01 13:00:00 | app_close | S003 | NULL |\n| 24 | 204 | 2024-03-01 14:00:00 | app_open | S004 | NULL |\n| 25 | 204 | 2024-03-01 14:05:00 | scroll | S004 | 600 |\n| 26 | 204 | 2024-03-01 14:08:00 | scroll | S004 | 700 |\n| 27 | 204 | 2024-03-01 14:10:00 | click | S004 | NULL |\n| 28 | 204 | 2024-03-01 14:12:00 | app_close | S004 | NULL |\n+----------+---------+---------------------+------------+------------+-------------+\n</pre>\n\n<p><strong>输出：</strong></p>\n\n<pre class=\"example-io\">\n+------------+---------+--------------------------+--------------+\n| session_id | user_id | session_duration_minutes | scroll_count |\n+------------+---------+--------------------------+--------------+\n| S001 | 201 | 35 | 6 |\n+------------+---------+--------------------------+--------------+\n</pre>\n\n<p><strong>解释：</strong></p>\n\n<ul>\n\t<li><strong>会话 S001 (User 201)</strong>:\n\n\t<ul>\n\t\t<li>时长：10:00:00 到 10:35:00 = 35 分钟（大于 30 分钟）</li>\n\t\t<li>滚动事件：6（至少 5 次）</li>\n\t\t<li>点击事件：0</li>\n\t\t<li>点击滚动比率：0/6 = 0.00（少于 0.20）</li>\n\t\t<li>购买数：0（没有购买）</li>\n\t\t<li>S001 是一个僵尸会话（满足所有条件）</li>\n\t</ul>\n\t</li>\n\t<li><strong>会话 S002 (User 202)</strong>:\n\t<ul>\n\t\t<li>时长：11:00:00 到 11:20:00 = 20 分钟（少于 30 分钟）</li>\n\t\t<li>有一次购买事件</li>\n\t\t<li>S002 不是一个僵尸会话</li>\n\t</ul>\n\t</li>\n\t<li><strong>会话 S003 (User 203)</strong>:\n\t<ul>\n\t\t<li>时长：12:00:00 到 13:00:00 = 60 分钟（超过 30 分钟）</li>\n\t\t<li>滚动事件：5（至少 5 次）</li>\n\t\t<li>点击事件：1</li>\n\t\t<li>点击滚动比率：1/5 = 0.20（不少于 0.20）</li>\n\t\t<li>购买数：0（没有购买）</li>\n\t\t<li>S003 不是一个僵尸会话（点击滚动比率等于 0.20，需要更少）。</li>\n\t</ul>\n\t</li>\n\t<li><strong>会话 S004 (User 204)</strong>:\n\t<ul>\n\t\t<li>时长：14:00:00 到 14:12:00 = 12 分钟（少于 30 分钟）</li>\n\t\t<li>滚动事件：2（少于 5 次）</li>\n\t\t<li>S004 不是一个僵尸会话</li>\n\t</ul>\n\t</li>\n</ul>\n\n<p>结果表按 scroll_count 降序排序，然后按 session_id 升序排序。</p>\n</div>\n",
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"code": "import pandas as pd\n\ndef find_zombie_sessions(app_events: pd.DataFrame) -> pd.DataFrame:\n ",
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"sampleTestCase": "{\"headers\":{\"app_events\":[\"event_id\",\"user_id\",\"event_timestamp\",\"event_type\",\"session_id\",\"event_value\"]},\"rows\":{\"app_events\":[[1,201,\"2024-03-01 10:00:00\",\"app_open\",\"S001\",null],[2,201,\"2024-03-01 10:05:00\",\"scroll\",\"S001\",500],[3,201,\"2024-03-01 10:10:00\",\"scroll\",\"S001\",750],[4,201,\"2024-03-01 10:15:00\",\"scroll\",\"S001\",600],[5,201,\"2024-03-01 10:20:00\",\"scroll\",\"S001\",800],[6,201,\"2024-03-01 10:25:00\",\"scroll\",\"S001\",550],[7,201,\"2024-03-01 10:30:00\",\"scroll\",\"S001\",900],[8,201,\"2024-03-01 10:35:00\",\"app_close\",\"S001\",null],[9,202,\"2024-03-01 11:00:00\",\"app_open\",\"S002\",null],[10,202,\"2024-03-01 11:02:00\",\"click\",\"S002\",null],[11,202,\"2024-03-01 11:05:00\",\"scroll\",\"S002\",400],[12,202,\"2024-03-01 11:08:00\",\"click\",\"S002\",null],[13,202,\"2024-03-01 11:10:00\",\"scroll\",\"S002\",350],[14,202,\"2024-03-01 11:15:00\",\"purchase\",\"S002\",50],[15,202,\"2024-03-01 11:20:00\",\"app_close\",\"S002\",null],[16,203,\"2024-03-01 12:00:00\",\"app_open\",\"S003\",null],[17,203,\"2024-03-01 12:10:00\",\"scroll\",\"S003\",1000],[18,203,\"2024-03-01 12:20:00\",\"scroll\",\"S003\",1200],[19,203,\"2024-03-01 12:25:00\",\"click\",\"S003\",null],[20,203,\"2024-03-01 12:30:00\",\"scroll\",\"S003\",800],[21,203,\"2024-03-01 12:40:00\",\"scroll\",\"S003\",900],[22,203,\"2024-03-01 12:50:00\",\"scroll\",\"S003\",1100],[23,203,\"2024-03-01 13:00:00\",\"app_close\",\"S003\",null],[24,204,\"2024-03-01 14:00:00\",\"app_open\",\"S004\",null],[25,204,\"2024-03-01 14:05:00\",\"scroll\",\"S004\",600],[26,204,\"2024-03-01 14:08:00\",\"scroll\",\"S004\",700],[27,204,\"2024-03-01 14:10:00\",\"click\",\"S004\",null],[28,204,\"2024-03-01 14:12:00\",\"app_close\",\"S004\",null]]}}",
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"metaData": "{\"mysql\":[\"CREATE TABLE app_events (\\n event_id INT,\\n user_id INT,\\n event_timestamp DATETIME,\\n event_type VARCHAR(20),\\n session_id VARCHAR(10),\\n event_value INT\\n)\"],\"mssql\":[\"CREATE TABLE app_events (\\n event_id INT,\\n user_id INT,\\n event_timestamp DATETIME,\\n event_type VARCHAR(20),\\n session_id VARCHAR(10),\\n event_value INT\\n)\"],\"oraclesql\":[\"CREATE TABLE app_events (\\n event_id NUMBER,\\n user_id NUMBER,\\n event_timestamp Date,\\n event_type VARCHAR2(20),\\n session_id VARCHAR2(10),\\n event_value NUMBER\\n)\",\"ALTER SESSION SET nls_date_format='YYYY-MM-DD HH24:MI:SS'\"],\"database\":true,\"name\":\"find_zombie_sessions\",\"postgresql\":[\"CREATE TABLE app_events (\\n event_id INT PRIMARY KEY,\\n user_id INT,\\n event_timestamp TIMESTAMP,\\n event_type VARCHAR(20),\\n session_id VARCHAR(10),\\n event_value INT\\n);\\n\"],\"pythondata\":[\"app_events = pd.DataFrame({\\n \\\"event_id\\\": pd.Series(dtype=\\\"int\\\"),\\n \\\"user_id\\\": pd.Series(dtype=\\\"int\\\"),\\n \\\"event_timestamp\\\": pd.Series(dtype=\\\"datetime64[ns]\\\"),\\n \\\"event_type\\\": pd.Series(dtype=\\\"string\\\"), # varchar -> string\\n \\\"session_id\\\": pd.Series(dtype=\\\"string\\\"), # varchar -> string\\n \\\"event_value\\\": pd.Series(dtype=\\\"int\\\")\\n})\"],\"database_schema\":{\"app_events\":{\"event_id\":\"INT\",\"user_id\":\"INT\",\"event_timestamp\":\"DATETIME\",\"event_type\":\"VARCHAR(20)\",\"session_id\":\"VARCHAR(10)\",\"event_value\":\"INT\"}}}",
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"CREATE TABLE app_events (\n event_id INT,\n user_id INT,\n event_timestamp DATETIME,\n event_type VARCHAR(20),\n session_id VARCHAR(10),\n event_value INT\n)",
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"Truncate table app_events",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('1', '201', '2024-03-01 10:00:00', 'app_open', 'S001', NULL)",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('2', '201', '2024-03-01 10:05:00', 'scroll', 'S001', '500')",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('3', '201', '2024-03-01 10:10:00', 'scroll', 'S001', '750')",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('4', '201', '2024-03-01 10:15:00', 'scroll', 'S001', '600')",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('5', '201', '2024-03-01 10:20:00', 'scroll', 'S001', '800')",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('6', '201', '2024-03-01 10:25:00', 'scroll', 'S001', '550')",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('7', '201', '2024-03-01 10:30:00', 'scroll', 'S001', '900')",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('8', '201', '2024-03-01 10:35:00', 'app_close', 'S001', NULL)",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('9', '202', '2024-03-01 11:00:00', 'app_open', 'S002', NULL)",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('10', '202', '2024-03-01 11:02:00', 'click', 'S002', NULL)",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('11', '202', '2024-03-01 11:05:00', 'scroll', 'S002', '400')",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('12', '202', '2024-03-01 11:08:00', 'click', 'S002', NULL)",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('13', '202', '2024-03-01 11:10:00', 'scroll', 'S002', '350')",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('14', '202', '2024-03-01 11:15:00', 'purchase', 'S002', '50')",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('15', '202', '2024-03-01 11:20:00', 'app_close', 'S002', NULL)",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('16', '203', '2024-03-01 12:00:00', 'app_open', 'S003', NULL)",
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"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('17', '203', '2024-03-01 12:10:00', 'scroll', 'S003', '1000')",
|
||
"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('18', '203', '2024-03-01 12:20:00', 'scroll', 'S003', '1200')",
|
||
"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('19', '203', '2024-03-01 12:25:00', 'click', 'S003', NULL)",
|
||
"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('20', '203', '2024-03-01 12:30:00', 'scroll', 'S003', '800')",
|
||
"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('21', '203', '2024-03-01 12:40:00', 'scroll', 'S003', '900')",
|
||
"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('22', '203', '2024-03-01 12:50:00', 'scroll', 'S003', '1100')",
|
||
"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('23', '203', '2024-03-01 13:00:00', 'app_close', 'S003', NULL)",
|
||
"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('24', '204', '2024-03-01 14:00:00', 'app_open', 'S004', NULL)",
|
||
"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('25', '204', '2024-03-01 14:05:00', 'scroll', 'S004', '600')",
|
||
"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('26', '204', '2024-03-01 14:08:00', 'scroll', 'S004', '700')",
|
||
"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('27', '204', '2024-03-01 14:10:00', 'click', 'S004', NULL)",
|
||
"insert into app_events (event_id, user_id, event_timestamp, event_type, session_id, event_value) values ('28', '204', '2024-03-01 14:12:00', 'app_close', 'S004', NULL)"
|
||
],
|
||
"enableRunCode": true,
|
||
"envInfo": "{\"mysql\":[\"MySQL\",\"<p>\\u7248\\u672c\\uff1a<code>MySQL 8.0<\\/code><\\/p>\"],\"mssql\":[\"MS SQL Server\",\"<p>mssql server 2019.<\\/p>\"],\"oraclesql\":[\"Oracle\",\"<p>Oracle Sql 11.2.<\\/p>\"],\"pythondata\":[\"Pandas\",\"<p>Python 3.10 with Pandas 2.2.2 and NumPy 1.26.4<\\/p>\"],\"postgresql\":[\"PostgreSQL\",\"<p>PostgreSQL 16<\\/p>\"]}",
|
||
"book": null,
|
||
"isSubscribed": false,
|
||
"isDailyQuestion": false,
|
||
"dailyRecordStatus": null,
|
||
"editorType": "CKEDITOR",
|
||
"ugcQuestionId": null,
|
||
"style": "LEETCODE",
|
||
"exampleTestcases": "{\"headers\":{\"app_events\":[\"event_id\",\"user_id\",\"event_timestamp\",\"event_type\",\"session_id\",\"event_value\"]},\"rows\":{\"app_events\":[[1,201,\"2024-03-01 10:00:00\",\"app_open\",\"S001\",null],[2,201,\"2024-03-01 10:05:00\",\"scroll\",\"S001\",500],[3,201,\"2024-03-01 10:10:00\",\"scroll\",\"S001\",750],[4,201,\"2024-03-01 10:15:00\",\"scroll\",\"S001\",600],[5,201,\"2024-03-01 10:20:00\",\"scroll\",\"S001\",800],[6,201,\"2024-03-01 10:25:00\",\"scroll\",\"S001\",550],[7,201,\"2024-03-01 10:30:00\",\"scroll\",\"S001\",900],[8,201,\"2024-03-01 10:35:00\",\"app_close\",\"S001\",null],[9,202,\"2024-03-01 11:00:00\",\"app_open\",\"S002\",null],[10,202,\"2024-03-01 11:02:00\",\"click\",\"S002\",null],[11,202,\"2024-03-01 11:05:00\",\"scroll\",\"S002\",400],[12,202,\"2024-03-01 11:08:00\",\"click\",\"S002\",null],[13,202,\"2024-03-01 11:10:00\",\"scroll\",\"S002\",350],[14,202,\"2024-03-01 11:15:00\",\"purchase\",\"S002\",50],[15,202,\"2024-03-01 11:20:00\",\"app_close\",\"S002\",null],[16,203,\"2024-03-01 12:00:00\",\"app_open\",\"S003\",null],[17,203,\"2024-03-01 12:10:00\",\"scroll\",\"S003\",1000],[18,203,\"2024-03-01 12:20:00\",\"scroll\",\"S003\",1200],[19,203,\"2024-03-01 12:25:00\",\"click\",\"S003\",null],[20,203,\"2024-03-01 12:30:00\",\"scroll\",\"S003\",800],[21,203,\"2024-03-01 12:40:00\",\"scroll\",\"S003\",900],[22,203,\"2024-03-01 12:50:00\",\"scroll\",\"S003\",1100],[23,203,\"2024-03-01 13:00:00\",\"app_close\",\"S003\",null],[24,204,\"2024-03-01 14:00:00\",\"app_open\",\"S004\",null],[25,204,\"2024-03-01 14:05:00\",\"scroll\",\"S004\",600],[26,204,\"2024-03-01 14:08:00\",\"scroll\",\"S004\",700],[27,204,\"2024-03-01 14:10:00\",\"click\",\"S004\",null],[28,204,\"2024-03-01 14:12:00\",\"app_close\",\"S004\",null]]}}",
|
||
"__typename": "QuestionNode"
|
||
}
|
||
}
|
||
} |