The document contains log data from user activities on a platform. There are three columns - user_id, event, and event_date. It logs the activities of 5 users over several days, including events like logins, posts, comments, views. It also includes some aggregated data on unique events and totals by user.

34. Column 1 Column 2 Column 3
Row 1
Row 2
Row 3
Row 4

44. user_id(int) event(string) event_date(string)
1 login_facebook 2019-05-14
1 write_posting 2019-05-14
1 write_comment 2019-05-14
1 view_posting 2019-05-14
1 view_posintg 2019-05-14
2 login_facebook 2019-05-14
2 view_posting 2019-05-14
2 view_posting 2019-05-14
2 write_comment 2019-05-14
2 logout 2019-05-14
2 login_facebook 2019-05-15
3 login_google 2019-05-15
3 write_posting 2019-05-15
3 view_posting 2019-05-15
3 purchase_item 2019-05-18
3 write_comment 2019-05-17
1 view_posting 2019-05-17
4 view_posintg 2019-05-17
5 purchase_item 2019-05-16

46. user_id event event_date
1 login_facebook 2019-05-14
1 write_posting 2019-05-14
1 write_comment 2019-05-14
1 view_posting 2019-05-14
1 view_posintg 2019-05-14

47. user_id event event_date
1 login_facebook 2019-05-14
1 write_posting 2019-05-14
1 write_comment 2019-05-14
1 view_posting 2019-05-14
1 view_posintg 2019-05-14

54. user_id event event_date unique total
1 login_facebook 2019-05-14 1 1
1 write_posting 2019-05-14 1 1
1 write_comment 2019-05-14 1 1
1 view_posting 2019-05-14 1 2

55. user_id event event_date unique total
1 login_facebook 2019-05-14 1 1
1 write_posting 2019-05-14 1 1
1 write_comment 2019-05-14 1 1
1 view_posting 2019-05-14 1 2

80. SELECT EXTRACT(DAY FROM DATE '2019-12-25') as the_day;
+---------+
| the_day |
+---------+
| 25 |
+---------+

81. SELECT DATE_ADD(DATE “2019-03-25", INTERVAL 5 DAY) as five_days_later;
+--------------------+
| five_days_later |
+--------------------+
| 2019-03-30 |
+--------------------+
SELECT DATE_DIFF(DATE '2010-07-07', DATE '2008-12-25', DAY) as days_diff;
+-----------+
| days_diff |
+-----------+
| 559 |
+-----------+

82. SELECT DATE_TRUNC(DATE '2008-12-25', MONTH) as month;
+------------+
| month |
+------------+
| 2008-12-01 |
+------------+

83. SELECT FORMAT_DATE("%x", DATE "2019-12-25") as US_format;
+------------+
| US_format |
+------------+
| 12/25/19 |
+------------+
SELECT PARSE_DATE("%x", "12/25/19") as parsed;
+------------+
| parsed |
+------------+
| 2019-12-25 |
+------------+

86. SELECT EXTRACT(HOUR FROM CAST(‘2019-12-25 14:00:00’ AS DATETIME) as hour;
+---------+
| hour |
+---------+
| 14 |
+---------+

102. Python

118. https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types

119. https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types

120. https://cloud.google.com/bigquery/docs/reference/standard-sql/arrays

121. https://cloud.google.com/bigquery/docs/reference/standard-sql/arrays

122. https://cloud.google.com/bigquery/docs/reference/standard-sql/arrays#arrays-and-aggregation

123. https://cloud.google.com/bigquery/docs/reference/standard-sql/arrays#arrays-and-aggregation

124. https://cloud.google.com/bigquery/docs/reference/standard-sql/arrays#arrays-and-aggregation

125. https://cloud.google.com/bigquery/docs/reference/standard-sql/arrays

126. https://cloud.google.com/bigquery/docs/reference/standard-sql/arrays

127. https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#struct-type

128. https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#struct-type

129.
https://cloud.google.com/bigquery/docs/reference/standard-sql/data-types#struct-type

131. https://cloud.google.com/bigquery/docs/reference/standard-sql/query-syntax#with_clause

132. https://cloud.google.com/bigquery/docs/reference/standard-sql/query-syntax#with_clause

133. https://cloud.google.com/bigquery/docs/views-intro

134. https://cloud.google.com/bigquery/docs/views-intro

135. https://cloud.google.com/bigquery/docs/views-intro

136. https://cloud.google.com/bigquery/docs/views-intro

137. https://cloud.google.com/bigquery/docs/views-intro

138. https://cloud.google.com/bigquery/docs/reference/standard-sql/analytic-function-concepts

139. https://cloud.google.com/bigquery/docs/reference/standard-sql/analytic-function-concepts

140. user_id visit_month
1004 1
1004 3
1004 7
1004 8
2112 3
2112 6
2112 7
3912 4

141. user_id visit_month next_visit_month
1004 1
1004 3
1004 7
1004 8
2112 3
2112 6
2112 7
3912 4

142. user_id visit_month next_visit_month
1004 1 3
1004 3 7
1004 7 8
1004 8 null
2112 3 6
2112 6 7
2112 7 null
3912 4 null

144. user_id visit_month
1004 1
1004 3
1004 7
1004 8
2112 3
2112 6
2112 7
3912 4
user_id visit_month
1004 1
1004 3
1004 7
1004 8
user_id visit_month
2112 3
2112 6
2112 7
user_id visit_month
3912 4

145. user_id visit_month
1004 1
1004 3
1004 7
1004 8
2112 3
2112 6
2112 7
3912 4
user_id visit_month
1004 1
1004 3
1004 7
1004 8
user_id visit_month
2112 3
2112 6
2112 7
user_id visit_month
3912 4

146. user_id visit_month
1004 1
1004 3
1004 7
1004 8
2112 3
2112 6
2112 7
3912 4
user_id visit_month
1004 1
1004 3
1004 7
1004 8
user_id visit_month
2112 3
2112 6
2112 7
user_id visit_month next_visit_month
1004 1 3
1004 3 7
1004 7 8
1004 8 null
2112 3 6
2112 6 7
2112 7 null
3912 4 null
user_id visit_month
3912 4

147. user_id visit_month next_visit_month next_two_
visit_month
1004 1 3 7
1004 3 7 8
1004 7 8 null
1004 8 null null
2112 3 6 7
2112 6 7 null
2112 7 null null
3912 4 null null

149. user_id visit_month
1004 1
1004 3
1004 7
1004 8
2112 3
2112 6
2112 7
3912 4

150. user_id visit_month
1004 1
1004 3
1004 7
1004 8
2112 3
2112 6
2112 7
3912 4

151. user_id visit_month
1004 1 null
1004 3 1
1004 7 3
1004 8 7
2112 3 null
2112 6 3
2112 7 6
3912 4 null

161. https://cloud.google.com/bigquery/docs/reference/standard-sql/analytic-function-concepts

162. datetime demand
2019-05-15 14:00:00 13 15
2019-05-15 15:00:00 16 16
2019-05-15 16:00:00 20 20
2019-05-15 17:00:00 25 29
2019-05-15 18:00:00 41 32
2019-05-15 19:00:00 31 34
2019-05-15 20:00:00 29 30

164. https://blog.statsbot.co/sql-window-functions-tutorial-b5075b87d129

165. https://blog.statsbot.co/sql-window-functions-tutorial-b5075b87d129

166. https://cloud.google.com/bigquery/docs/reference/standard-sql/json_functions

167. https://cloud.google.com/bigquery/docs/reference/standard-sql/json_functions

168.
https://cloud.google.com/bigquery/docs/reference/standard-sql/user-defined-functions

169. https://cloud.google.com/bigquery/docs/reference/standard-sql/user-defined-functions#sql-udf-structure

170. https://cloud.google.com/bigquery/docs/reference/standard-sql/user-defined-functions#supported-external-udf-languages

171. https://cloud.google.com/bigquery/docs/reference/standard-sql/user-defined-functions#including-external-libraries

173.
https://cloud.google.com/bigquery/docs/partitioned-tables

174.
https://cloud.google.com/bigquery/docs/querying-wildcard-tables

175. https://cloud.google.com/bigquery/docs/creating-column-partitions

176. https://cloud.google.com/bigquery/docs/querying-partitioned-tables

177.
https://cloud.google.com/bigquery/docs/querying-partitioned-tables

194. https://cloud.google.com/bigquery/docs/scheduling-queries

195. https://cloud.google.com/bigquery/docs/scheduling-queries

196. https://cloud.google.com/bigquery/docs/scheduling-queries

197. https://cloud.google.com/bigquery/docs/scheduling-queries

198. https://cloud.google.com/bigquery/docs/scheduling-queries

199. https://cloud.google.com/bigquery/docs/scheduling-queries

200. https://cloud.google.com/bigquery/docs/scheduling-queries

201. https://cloud.google.com/bigquery/docs/scheduling-queries

202. https://cloud.google.com/bigquery/docs/scheduling-queries

210. [ GS URL ]
[ Table ]
[ ( ]
[ , ]
[ ]

232. https://support.google.com/firebase/answer/7029846

233. https://support.google.com/firebase/answer/7029846

234. https://support.google.com/firebase/answer/6317485

235. https://support.google.com/firebase/answer/6317485

239. https://medium.com/firebase-developers/using-the-unnest-function-in-bigquery-to-analyze-event-parameters-in-
analytics-fb828f890b42

240. https://medium.com/firebase-developers/using-the-unnest-function-in-bigquery-to-analyze-event-parameters-in-
analytics-fb828f890b42

249. https://www.slideshare.net/lynnlangit/google-cloud-and-data-pipeline-patterns

250. https://medium.com/teads-engineering/give-meaning-to-100-billion-analytics-events-a-day-d6ba09aa8f44

251. https://wecode.wepay.com/posts/bigquery-wepay

266. https://cloud.google.com/bigquery/docs/reference/standard-sql/query-syntax#sql-syntax