我收到了一封电子邮件，其中包含将我以前的 Firebase 表格迁移到新架构的说明。他们指出了以下说明：
- https://support.google.com/analytics/answer/7029846?#migrationscript
但我更愿意：
- 与其运行 bash 脚本，我宁愿只运行一个执行迁移的查询。
- 与其创建许多新表，我宁愿将所有以前的结果移动到新的日期分区表中。
我采用了文档上的脚本并进行了一些更改。
- 查看所有
--Fh评论。这些是我的修改。 - 选择目标表。
- 选择安卓和 IOS 的日期范围。
- 请注意，我正在添加一个带有真实时间戳的新列，用于分区(以及您的方便)。
- 您不会获得多个新表，而是只会获得一个 - 但按日期分区。
修改后的脚本：
#standardSQL
CREATE OR REPLACE TABLE `fh-bigquery.deleting.delete`
PARTITION BY DATE(ts)
AS
WITH sources AS ( --Fh
SELECT * FROM (
SELECT *, _table_suffix event_date, 'ANDROID' operating_system
FROM `firebase-public-project.com_firebase_demo_ANDROID.app_events_*`
UNION ALL SELECT *, _table_suffix event_date, 'IOS' operating_system
FROM `firebase-public-project.com_firebase_demo_IOS.app_events_*`
)
WHERE event_date BETWEEN '20180503' AND '20180504' --Fh: choose your timerange
)
SELECT
event_date, --Fh: extracted from original table name
TIMESTAMP_MICROS(event.timestamp_micros) ts, --Fh: adding a real timestamp column
event.timestamp_micros AS event_timestamp,
event.previous_timestamp_micros AS event_previous_timestamp,
event.name AS event_name,
event.value_in_usd AS event_value_in_usd,
user_dim.bundle_info.bundle_sequence_id AS event_bundle_sequence_id,
user_dim.bundle_info.server_timestamp_offset_micros as event_server_timestamp_offset,
(
SELECT
ARRAY_AGG(STRUCT(event_param.key AS key,
STRUCT(event_param.value.string_value AS string_value,
event_param.value.int_value AS int_value,
event_param.value.double_value AS double_value,
event_param.value.float_value AS float_value) AS value))
FROM
UNNEST(event.params) AS event_param) AS event_params,
user_dim.first_open_timestamp_micros AS user_first_touch_timestamp,
user_dim.user_id AS user_id,
user_dim.app_info.app_instance_id AS user_pseudo_id,
"" AS stream_id,
user_dim.app_info.app_platform AS platform,
STRUCT( user_dim.ltv_info.revenue AS revenue,
user_dim.ltv_info.currency AS currency ) AS user_ltv,
STRUCT( user_dim.traffic_source.user_acquired_campaign AS name,
user_dim.traffic_source.user_acquired_medium AS medium,
user_dim.traffic_source.user_acquired_source AS source ) AS traffic_source,
STRUCT( user_dim.geo_info.continent AS continent,
user_dim.geo_info.country AS country,
user_dim.geo_info.region AS region,
user_dim.geo_info.city AS city ) AS geo,
STRUCT( user_dim.device_info.device_category AS category,
user_dim.device_info.mobile_brand_name,
user_dim.device_info.mobile_model_name,
user_dim.device_info.mobile_marketing_name,
user_dim.device_info.device_model AS mobile_os_hardware_model,
operating_system, --Fh
user_dim.device_info.platform_version AS operating_system_version,
user_dim.device_info.device_id AS vendor_id,
user_dim.device_info.resettable_device_id AS advertising_id,
user_dim.device_info.user_default_language AS language,
user_dim.device_info.device_time_zone_offset_seconds AS time_zone_offset_seconds,
IF(user_dim.device_info.limited_ad_tracking, "Yes", "No") AS is_limited_ad_tracking ) AS device,
STRUCT( user_dim.app_info.app_id AS id,
'app_id' AS firebase_app_id, --Fh: choose your app id
user_dim.app_info.app_version AS version,
user_dim.app_info.app_store AS install_source ) AS app_info,
( SELECT ARRAY_AGG(STRUCT(user_property.key AS key,
STRUCT(user_property.value.value.string_value AS string_value,
user_property.value.value.int_value AS int_value,
user_property.value.value.double_value AS double_value,
user_property.value.value.float_value AS float_value,
user_property.value.set_timestamp_usec AS set_timestamp_micros ) AS value))
FROM UNNEST(user_dim.user_properties) AS user_property
) AS user_properties
FROM sources -- Fh
, UNNEST(event_dim) AS event