举个例子,
event_dim.name = "Start_Level"
event_dim.params.key = "Chapter_Name"
event_dim.params.value.string_value = "chapter_1" (or "chapter_2" or "chapter_3" and so on)
event_dim.params.key = "Level"
event_dim.params.value.int_value = 1 or 2 or 3 or 4 and so on
event_dim.params.key = "Opening_Balance"
event_dim.params.value = 1000 or 1200 or 300 or so on
如果我愿意,如何取出数据: - 查看仅为event_dim.params.string_value =“chapter_1”播放“Level”的唯一用户(意味着第1章中的级别) - 查看每个“级别”的“Opening_Balance”,仅查看event_dim.params.key =“Chapter_Name”和event_dim.params.value.string_value =“chapter_2”
章节中的级别目前,我正在尝试按照以下方式来获取我认为不会给我正确数据的数据。我试图为在特定日期(通过first_open)和特定来源之间安装游戏的用户取出关卡数据。:
SELECT
COUNT(DISTINCT(app_instance)),
event_value.int_value
FROM (
SELECT
user_dim.app_info.app_instance_id AS app_instance,
event.name AS event,
(
SELECT
user_prop.value.value.int_value
FROM
UNNEST(user_dim.user_properties) AS user_prop
WHERE
user_prop.key = 'first_open_time') AS first_open,
params.key AS event_param,
params.value AS event_value
FROM
`app_package.app_events_*`,
UNNEST(event_dim) AS event,
UNNEST(event.params) AS params
WHERE
event.name = "start_level"
AND user_dim.traffic_source.user_acquired_source = "source"
AND params.key != 'firebase_event_origin'
AND params.key != 'firebase_screen_class'
AND params.key != 'firebase_screen_id' )
WHERE
event_param = "Level"
AND (first_open >= 1516579200000 AND first_open <= 1516924800000)
GROUP BY
event_value.int_value
但是,我无法隔离事件中chapter_name =“chapter_1”时特定的事件。 (不幸的是我不知道怎么做,因此问题)
更新:(根据Mikhail的要求添加了一些其他信息)
示例输入事件如下:
+-----------------+-------------+-----------------+--------------+-----------+
| app_instance_id | event_name | param_key | string_value | int_value |
+-----------------+-------------+-----------------+--------------+-----------+
| 100001 | start_level | chapter_name | chapter_1 | null |
| | | level | null | 1 |
| | | opening_balance | null | 2000 |
| | start_level | chapter_name | chapter_1 | null |
| | | level | null | 2 |
| | | opening_balance | null | 2500 |
| | start_level | chapter_name | chapter_1 | null |
| | | level | null | 2 |
| | | opening_balance | null | 2750 |
| | start_level | chapter_name | chapter_1 | null |
| | | level | null | 3 |
| | | opening_balance | null | 3000 |
| | start_level | chapter_name | chapter_2 | null |
| | | level | null | 1 |
| | | opening_balance | null | 3100 |
| | start_level | chapter_name | chapter_2 | null |
| | | level | null | 2 |
| | | opening_balance | null | 3500 |
| | start_level | chapter_name | chapter_2 | null |
| | | level | null | 3 |
| | | opening_balance | null | 3800 |
| 100002 | start_level | chapter_name | chapter_1 | null |
| | | level | null | 1 |
| | | opening_balance | null | 2000 |
| | start_level | chapter_name | chapter_1 | null |
| | | level | null | 2 |
| | | opening_balance | null | 2250 |
| | start_level | chapter_name | chapter_1 | null |
| | | level | null | 2 |
| | | opening_balance | null | 2400 |
| | start_level | chapter_name | chapter_1 | null |
| | | level | null | 3 |
| | | opening_balance | null | 2800 |
| | start_level | chapter_name | chapter_2 | null |
| | | level | null | 1 |
| | | opening_balance | null | 3000 |
| | start_level | chapter_name | chapter_2 | null |
| | | level | null | 2 |
| | | opening_balance | null | 3200 |
+-----------------+-------------+-----------------+--------------+-----------+
所需输出如下:
+-----------+-------+--------------+-------------------+---------------+
| Chapter | Level | Unique Users | Total Level Start | Avg. Open Bal |
+-----------+-------+--------------+-------------------+---------------+
| chapter_1 | 1 | 2 | 2 | 2000 |
| chapter_1 | 2 | 2 | 3 | 2383 |
| chapter_1 | 3 | 2 | 3 | 2850 |
| chapter_2 | 1 | 2 | 2 | 3050 |
| chapter_2 | 2 | 2 | 2 | 3350 |
| chapter_2 | 3 | 1 | 1 | 3800 |
+-----------+-------+--------------+-------------------+---------------+
答案 0 :(得分:0)
对于正在寻找此问题答案的任何人,您可以尝试以下标准的SQL查询:
SELECT
chapter,
level,
count(distinct id) as Unique_Users,
count(id) as Level_start,
avg(opening_balance) as Avg_Open_Bal,
FROM(
SELECT
user_dim.app_info.app_instance_id AS id,
event.date,
event.name,
(SELECT value.string_value FROM UNNEST(event.params) WHERE key = "chapter_name") AS chapter,
(SELECT value.int_value FROM UNNEST(event.params) WHERE key = "level") AS level,
(SELECT value.int_value FROM UNNEST(event.params) WHERE key = "opening_coin_balance") AS open_bal
FROM
`<table_name>`,
UNNEST(event_dim) AS event
WHERE
event.name = "start_level"
)
GROUP BY
chapter,
level