<p>Table: <code>Activity</code></p> <pre> +---------------+---------+ | Column Name | Type | +---------------+---------+ | user_id | int | | session_id | int | | activity_date | date | | activity_type | enum | +---------------+---------+ There is no primary key for this table, it may have duplicate rows. The activity_type column is an ENUM of type ('open_session', 'end_session', 'scroll_down', 'send_message'). The table shows the user activities for a social media website. Note that each session belongs to exactly one user. </pre> <p> </p> <p>Write an SQL query to find the daily active user count for a period of <code>30</code> days ending <code>2019-07-27</code> inclusively. A user was active on someday if they made at least one activity on that day.</p> <p>Return the result table in <strong>any order</strong>.</p> <p>The query result format is in the following example.</p> <p> </p> <p><strong>Example 1:</strong></p> <pre> <strong>Input:</strong> Activity table: +---------+------------+---------------+---------------+ | user_id | session_id | activity_date | activity_type | +---------+------------+---------------+---------------+ | 1 | 1 | 2019-07-20 | open_session | | 1 | 1 | 2019-07-20 | scroll_down | | 1 | 1 | 2019-07-20 | end_session | | 2 | 4 | 2019-07-20 | open_session | | 2 | 4 | 2019-07-21 | send_message | | 2 | 4 | 2019-07-21 | end_session | | 3 | 2 | 2019-07-21 | open_session | | 3 | 2 | 2019-07-21 | send_message | | 3 | 2 | 2019-07-21 | end_session | | 4 | 3 | 2019-06-25 | open_session | | 4 | 3 | 2019-06-25 | end_session | +---------+------------+---------------+---------------+ <strong>Output:</strong> +------------+--------------+ | day | active_users | +------------+--------------+ | 2019-07-20 | 2 | | 2019-07-21 | 2 | +------------+--------------+ <strong>Explanation:</strong> Note that we do not care about days with zero active users. </pre>