behavior_basic_events Normal 0 / ID_BATCH Y ID_BATCH CHANNEL_ID Y CHANNEL_ID TRANSNAME Y TRANSNAME STATUS Y STATUS LINES_READ Y LINES_READ LINES_WRITTEN Y LINES_WRITTEN LINES_UPDATED Y LINES_UPDATED LINES_INPUT Y LINES_INPUT LINES_OUTPUT Y LINES_OUTPUT LINES_REJECTED Y LINES_REJECTED ERRORS Y ERRORS STARTDATE Y STARTDATE ENDDATE Y ENDDATE LOGDATE Y LOGDATE DEPDATE Y DEPDATE REPLAYDATE Y REPLAYDATE LOG_FIELD Y LOG_FIELD EXECUTING_SERVER N EXECUTING_SERVER EXECUTING_USER N EXECUTING_USER CLIENT N CLIENT
ID_BATCH Y ID_BATCH SEQ_NR Y SEQ_NR LOGDATE Y LOGDATE TRANSNAME Y TRANSNAME STEPNAME Y STEPNAME STEP_COPY Y STEP_COPY LINES_READ Y LINES_READ LINES_WRITTEN Y LINES_WRITTEN LINES_UPDATED Y LINES_UPDATED LINES_INPUT Y LINES_INPUT LINES_OUTPUT Y LINES_OUTPUT LINES_REJECTED Y LINES_REJECTED ERRORS Y ERRORS INPUT_BUFFER_ROWS Y INPUT_BUFFER_ROWS OUTPUT_BUFFER_ROWS Y OUTPUT_BUFFER_ROWS
ID_BATCH Y ID_BATCH CHANNEL_ID Y CHANNEL_ID LOG_DATE Y LOG_DATE LOGGING_OBJECT_TYPE Y LOGGING_OBJECT_TYPE OBJECT_NAME Y OBJECT_NAME OBJECT_COPY Y OBJECT_COPY REPOSITORY_DIRECTORY Y REPOSITORY_DIRECTORY FILENAME Y FILENAME OBJECT_ID Y OBJECT_ID OBJECT_REVISION Y OBJECT_REVISION PARENT_CHANNEL_ID Y PARENT_CHANNEL_ID ROOT_CHANNEL_ID Y ROOT_CHANNEL_ID
ID_BATCH Y ID_BATCH CHANNEL_ID Y CHANNEL_ID LOG_DATE Y LOG_DATE TRANSNAME Y TRANSNAME STEPNAME Y STEPNAME STEP_COPY Y STEP_COPY LINES_READ Y LINES_READ LINES_WRITTEN Y LINES_WRITTEN LINES_UPDATED Y LINES_UPDATED LINES_INPUT Y LINES_INPUT LINES_OUTPUT Y LINES_OUTPUT LINES_REJECTED Y LINES_REJECTED ERRORS Y ERRORS LOG_FIELD N LOG_FIELD
ID_BATCH Y ID_BATCH CHANNEL_ID Y CHANNEL_ID LOG_DATE Y LOG_DATE METRICS_DATE Y METRICS_DATE METRICS_CODE Y METRICS_CODE METRICS_DESCRIPTION Y METRICS_DESCRIPTION METRICS_SUBJECT Y METRICS_SUBJECT METRICS_TYPE Y METRICS_TYPE METRICS_VALUE Y METRICS_VALUE
0.0 0.0 10000 50 50 N Y 50000 Y N 1000 100 - 2020/02/25 14:03:43.587 - 2020/02/25 14:03:43.587 H4sIAAAAAAAAAAMAAAAAAAAAAAA= N epdc_analysis_source ${db.mysql.epdc.source.host} MYSQL Native ${esua.epdc.analysis.database} ${db.mysql.epdc.source.port} ${db.mysql.epdc.source.username} ${db.mysql.epdc.source.password} EXTRA_OPTION_MYSQL.characterEncoding utf8 EXTRA_OPTION_MYSQL.useSSL false FORCE_IDENTIFIERS_TO_LOWERCASE N FORCE_IDENTIFIERS_TO_UPPERCASE N IS_CLUSTERED N PORT_NUMBER ${db.mysql.epdc.source.port} PRESERVE_RESERVED_WORD_CASE Y QUOTE_ALL_FIELDS N STREAM_RESULTS Y SUPPORTS_BOOLEAN_DATA_TYPE Y SUPPORTS_TIMESTAMP_DATA_TYPE Y USE_POOLING N epdc_analysis_target ${db.mysql.epdc.analysis.target.host} MYSQL Native ${esua.epdc.analysis.database} ${db.mysql.epdc.analysis.target.port} ${db.mysql.epdc.analysis.target.username} ${db.mysql.epdc.analysis.target.password} EXTRA_OPTION_MYSQL.characterEncoding utf8 EXTRA_OPTION_MYSQL.useSSL false FORCE_IDENTIFIERS_TO_LOWERCASE N FORCE_IDENTIFIERS_TO_UPPERCASE N IS_CLUSTERED N PORT_NUMBER ${db.mysql.epdc.analysis.target.port} PRESERVE_RESERVED_WORD_CASE Y QUOTE_ALL_FIELDS N STREAM_RESULTS Y SUPPORTS_BOOLEAN_DATA_TYPE Y SUPPORTS_TIMESTAMP_DATA_TYPE Y USE_POOLING N 字段选择 表输出 Y 表输入 字段选择 Y 字段选择 SelectValues Y 1 none ID GRID_ID ISSUE_PUBLISH_TIMES USER_PUBLISH_TIMES PARTY_PUBLISH_TIMES USER_LIKE_TIME USER_OPPOSE_TIMES PARTY_LIKE_TIME PARTY_OPPOSE_TIMES USER_COMMENT_TIMES PARTY_COMMENT_TIMES USER_TOITEM_TIMES USER_EVALUATE_TIMES USER_GOOD_TIMES PARTY_TOITEM_TIMES USER_FINISH_TIMES PARTY_GOOD_TIMES PARTY_EVALUATE_TIMES PARTY_FINISH_TIMES STATISTICS_DATE CREATED_TIME UPDATED_TIME N 560 272 Y 表输入 TableInput Y 1 none epdc_analysis_source select REPLACE(MD5(UUID()),'-','') AS ID, total.GRID_ID, SUM(total.ISSUE_PUBLISH_TIMES) AS ISSUE_PUBLISH_TIMES, SUM(total.USER_PUBLISH_TIMES) AS USER_PUBLISH_TIMES, SUM(total.PARTY_PUBLISH_TIMES) AS PARTY_PUBLISH_TIMES, SUM(total.USER_LIKE_TIME) AS USER_LIKE_TIME, SUM(total.USER_OPPOSE_TIMES) AS USER_OPPOSE_TIMES, SUM(total.PARTY_LIKE_TIME) AS PARTY_LIKE_TIME, SUM(total.PARTY_OPPOSE_TIMES) AS PARTY_OPPOSE_TIMES, SUM(total.USER_COMMENT_TIMES) AS USER_COMMENT_TIMES, SUM(total.PARTY_COMMENT_TIMES) AS PARTY_COMMENT_TIMES, SUM(total.USER_TOITEM_TIMES) AS USER_TOITEM_TIMES, SUM(total.USER_EVALUATE_TIMES) AS USER_EVALUATE_TIMES, SUM(total.USER_GOOD_TIMES) AS USER_GOOD_TIMES, SUM(total.PARTY_TOITEM_TIMES) AS PARTY_TOITEM_TIMES, SUM(total.USER_FINISH_TIMES) AS USER_FINISH_TIMES, SUM(total.PARTY_GOOD_TIMES) AS PARTY_GOOD_TIMES, SUM(total.PARTY_EVALUATE_TIMES) AS PARTY_EVALUATE_TIMES, SUM(total.PARTY_FINISH_TIMES) AS PARTY_FINISH_TIMES, total.CREATED_TIME AS STATISTICS_DATE, NOW() AS CREATED_TIME,NOW() AS UPDATED_TIME from ( select mei.GRID_ID, COUNT(id) AS ISSUE_PUBLISH_TIMES, COUNT(IS_PARTY_MEMBER=0 OR NULL) AS USER_PUBLISH_TIMES, COUNT(IS_PARTY_MEMBER=1 OR NULL) AS PARTY_PUBLISH_TIMES, 0 AS USER_LIKE_TIME, 0 AS USER_OPPOSE_TIMES, 0 AS PARTY_LIKE_TIME, 0 AS PARTY_OPPOSE_TIMES, 0 AS USER_COMMENT_TIMES, 0 AS PARTY_COMMENT_TIMES, 0 AS USER_TOITEM_TIMES, 0 AS USER_EVALUATE_TIMES, 0 AS USER_GOOD_TIMES, 0 AS PARTY_TOITEM_TIMES, 0 AS PARTY_EVALUATE_TIMES, 0 AS PARTY_GOOD_TIMES, 0 AS USER_FINISH_TIMES, 0 AS PARTY_FINISH_TIMES, date_format(mei.DISTRIBUTE_TIME,'%Y-%m-%d') AS CREATED_TIME from meta_epdc_issue mei where mei.DEL_FLAG=0 AND mei.CREATED_TIME BETWEEN DATE_SUB(CURDATE(), interval ${statDays} day) AND DATE_SUB(CURDATE(), interval (${statDays}-1) day) GROUP BY mei.GRID_ID,date_format(mei.DISTRIBUTE_TIME,'%Y-%m-%d') UNION ALL select attitude_total.GRID_ID, 0 AS ISSUE_PUBLISH_TIMES, 0 AS USER_PUBLISH_TIMES, 0 AS PARTY_PUBLISH_TIMES, SUM(attitude_total.USER_LIKE_TIME) AS USER_LIKE_TIME, SUM(attitude_total.USER_OPPOSE_TIMES) AS USER_OPPOSE_TIMES, SUM(attitude_total.PARTY_LIKE_TIME) AS PARTY_LIKE_TIME, SUM(attitude_total.PARTY_OPPOSE_TIMES) AS PARTY_OPPOSE_TIMES, 0 AS USER_COMMENT_TIMES, 0 AS PARTY_COMMENT_TIMES, 0 AS USER_TOITEM_TIMES, 0 AS USER_EVALUATE_TIMES, 0 AS USER_GOOD_TIMES, 0 AS PARTY_TOITEM_TIMES, 0 AS PARTY_EVALUATE_TIMES, 0 AS PARTY_GOOD_TIMES, 0 AS USER_FINISH_TIMES, 0 AS PARTY_FINISH_TIMES, attitude_total.CREATED_TIME from ( select mee.GRID_ID, COUNT(cua.ATTITUDE_FLAG=0 and eec.PARTY_FLAG=0 OR NULL) AS USER_LIKE_TIME, COUNT(cua.ATTITUDE_FLAG=1 and eec.PARTY_FLAG=0 OR NULL) AS USER_OPPOSE_TIMES, COUNT(cua.ATTITUDE_FLAG=0 and eec.PARTY_FLAG=1 OR NULL) AS PARTY_LIKE_TIME, COUNT(cua.ATTITUDE_FLAG=1 and eec.PARTY_FLAG=1 OR NULL) AS PARTY_OPPOSE_TIMES, date_format(cua.CREATED_TIME,'%Y-%m-%d') AS CREATED_TIME from meta_epdc_event_comment_user_attitude cua left join meta_epdc_event_comment eec on eec.id=cua.EVENT_COMMENT_ID left join meta_epdc_events mee on mee.ID=eec.EVENT_ID where cua.DEL_FLAG=0 AND cua.CREATED_TIME BETWEEN DATE_SUB(CURDATE(), interval ${statDays} day) AND DATE_SUB(CURDATE(), interval (${statDays}-1) day) group by mee.GRID_ID,date_format(cua.CREATED_TIME,'%Y-%m-%d') UNION ALL select mee.GRID_ID, COUNT(eua.ATTITUDE_FLAG=0 and mee.IS_PARTY_MEMBER=0 OR NULL) AS USER_LIKE_TIME, COUNT(eua.ATTITUDE_FLAG=1 and mee.IS_PARTY_MEMBER=0 OR NULL) AS USER_OPPOSE_TIMES, COUNT(eua.ATTITUDE_FLAG=0 and mee.IS_PARTY_MEMBER=1 OR NULL) AS PARTY_LIKE_TIME, COUNT(eua.ATTITUDE_FLAG=1 and mee.IS_PARTY_MEMBER=1 OR NULL) AS PARTY_OPPOSE_TIMES, date_format(eua.CREATED_TIME,'%Y-%m-%d') AS CREATED_TIME from meta_epdc_event_user_attitude eua left join meta_epdc_events mee on mee.id=eua.EVENT_ID WHERE eua.DEL_FLAG=0 AND eua.CREATED_TIME BETWEEN DATE_SUB(CURDATE(), interval ${statDays} day) AND DATE_SUB(CURDATE(), interval (${statDays}-1) day) group by mee.GRID_ID,date_format(eua.CREATED_TIME,'%Y-%m-%d') )attitude_total group by attitude_total.GRID_ID,attitude_total.CREATED_TIME UNION ALL select mee.GRID_ID, 0 AS ISSUE_PUBLISH_TIMES, 0 AS USER_PUBLISH_TIMES, 0 AS PARTY_PUBLISH_TIMES, 0 AS USER_LIKE_TIME, 0 AS USER_OPPOSE_TIMES, 0 AS PARTY_LIKE_TIME, 0 AS PARTY_OPPOSE_TIMES, COUNT(eec.PARTY_FLAG=0 OR NULL) AS USER_COMMENT_TIMES, COUNT(eec.PARTY_FLAG=1 OR NULL) AS PARTY_COMMENT_TIMES, 0 AS USER_TOITEM_TIMES, 0 AS USER_EVALUATE_TIMES, 0 AS USER_GOOD_TIMES, 0 AS PARTY_TOITEM_TIMES, 0 AS PARTY_EVALUATE_TIMES, 0 AS PARTY_GOOD_TIMES, 0 AS USER_FINISH_TIMES, 0 AS PARTY_FINISH_TIMES, date_format(eec.CREATED_TIME,'%Y-%m-%d') AS CREATED_TIME from meta_epdc_event_comment eec left join meta_epdc_events mee on mee.id=eec.EVENT_ID where eec.DEL_FLAG=0 AND eec.CREATED_TIME BETWEEN DATE_SUB(CURDATE(), interval ${statDays} day) AND DATE_SUB(CURDATE(), interval (${statDays}-1) day) group by mee.GRID_ID,date_format(eec.CREATED_TIME,'%Y-%m-%d') UNION ALL select mei.GRID_ID, 0 AS ISSUE_PUBLISH_TIMES, 0 AS USER_PUBLISH_TIMES, 0 AS PARTY_PUBLISH_TIMES, 0 AS USER_LIKE_TIME, 0 AS USER_OPPOSE_TIMES, 0 AS PARTY_LIKE_TIME, 0 AS PARTY_OPPOSE_TIMES, 0 AS USER_COMMENT_TIMES, 0 AS PARTY_COMMENT_TIMES, COUNT( IS_PARTY_MEMBER=0 OR NULL) AS USER_TOITEM_TIMES, COUNT(EVALUATION_SCORE IS NOT NULL AND IS_PARTY_MEMBER=0 OR NULL) AS USER_EVALUATE_TIMES, COUNT(EVALUATION_SCORE IS NOT NULL AND EVALUATION_SCORE != 0 AND IS_PARTY_MEMBER=0 OR NULL) AS USER_GOOD_TIMES, COUNT(IS_PARTY_MEMBER=1 OR NULL) AS PARTY_TOITEM_TIMES, COUNT(EVALUATION_SCORE IS NOT NULL AND IS_PARTY_MEMBER=1 OR NULL) AS PARTY_EVALUATE_TIMES, COUNT(EVALUATION_SCORE IS NOT NULL AND EVALUATION_SCORE != 0 AND IS_PARTY_MEMBER=1 OR NULL) AS PARTY_GOOD_TIMES, 0 AS USER_FINISH_TIMES, 0 AS PARTY_FINISH_TIMES, date_format(mei.CREATED_TIME,'%Y-%m-%d') AS CREATED_TIME from meta_epdc_item mei where mei.DEL_FLAG=0 AND mei.CREATED_TIME BETWEEN DATE_SUB(CURDATE(), interval ${statDays} day) AND DATE_SUB(CURDATE(), interval (${statDays}-1) day) group by mei.GRID_ID,date_format(mei.CREATED_TIME,'%Y-%m-%d') UNION ALL SELECT mei.GRID_ID, 0 AS ISSUE_PUBLISH_TIMES, 0 AS USER_PUBLISH_TIMES, 0 AS PARTY_PUBLISH_TIMES, 0 AS USER_LIKE_TIME, 0 AS USER_OPPOSE_TIMES, 0 AS PARTY_LIKE_TIME, 0 AS PARTY_OPPOSE_TIMES, 0 AS USER_COMMENT_TIMES, 0 AS PARTY_COMMENT_TIMES, 0 AS USER_TOITEM_TIMES, 0 AS USER_EVALUATE_TIMES, 0 AS USER_GOOD_TIMES, 0 AS PARTY_TOITEM_TIMES, 0 AS PARTY_EVALUATE_TIMES, 0 AS PARTY_GOOD_TIMES, COUNT(STATE=10 and IS_PARTY_MEMBER=0 OR NULL) AS USER_FINISH_TIMES, COUNT(STATE=10 and IS_PARTY_MEMBER=1 OR NULL) AS PARTY_FINISH_TIMES, date_format(IHP.CREATED_TIME,'%Y-%m-%d') AS CREATED_TIME FROM meta_epdc_item_handle_process ihp left join meta_epdc_item mei on ihp.ITEM_ID=mei.ID where ihp.DEL_FLAG=0 AND ihp.CREATED_TIME BETWEEN DATE_SUB(CURDATE(), interval ${statDays} day) AND DATE_SUB(CURDATE(), interval (${statDays}-1) day) group by mei.GRID_ID,date_format(ihp.CREATED_TIME,'%Y-%m-%d') )total group by total.GRID_ID,total.CREATED_TIME ORDER BY total.CREATED_TIME 0 N Y N N String normal ID 32 -1 表输入 ID . , none N Y 0 N N N zh_CN Asia/Shanghai N Integer normal GRID_ID 15 0 表输入 GRID_ID ####0;-####0 . , none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal ISSUE_PUBLISH_TIMES 42 0 表输入 ISSUE_PUBLISH_TIMES ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal USER_PUBLISH_TIMES 42 0 表输入 USER_PUBLISH_TIMES ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal PARTY_PUBLISH_TIMES 42 0 表输入 PARTY_PUBLISH_TIMES ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal USER_LIKE_TIME 64 0 表输入 USER_LIKE_TIME ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal USER_OPPOSE_TIMES 64 0 表输入 USER_OPPOSE_TIMES ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal PARTY_LIKE_TIME 64 0 表输入 PARTY_LIKE_TIME ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal PARTY_OPPOSE_TIMES 64 0 表输入 PARTY_OPPOSE_TIMES ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal USER_COMMENT_TIMES 41 0 表输入 USER_COMMENT_TIMES ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal PARTY_COMMENT_TIMES 41 0 表输入 PARTY_COMMENT_TIMES ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal USER_TOITEM_TIMES 41 0 表输入 USER_TOITEM_TIMES ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal USER_EVALUATE_TIMES 41 0 表输入 USER_EVALUATE_TIMES ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal USER_GOOD_TIMES 41 0 表输入 USER_GOOD_TIMES ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal PARTY_TOITEM_TIMES 41 0 表输入 PARTY_TOITEM_TIMES ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal USER_FINISH_TIMES 41 0 表输入 USER_FINISH_TIMES ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal PARTY_GOOD_TIMES 41 0 表输入 PARTY_GOOD_TIMES ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal PARTY_EVALUATE_TIMES 41 0 表输入 PARTY_EVALUATE_TIMES ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N BigNumber normal PARTY_FINISH_TIMES 41 0 表输入 PARTY_FINISH_TIMES ######0.0###################;-######0.0################### . none N Y 0 N N N zh_CN Asia/Shanghai N String normal STATISTICS_DATE 10 -1 表输入 STATISTICS_DATE . , none N Y 0 N N N zh_CN Asia/Shanghai N Timestamp normal CREATED_TIME 0 -1 表输入 CREATED_TIME . , none N Y 0 N N N zh_CN Asia/Shanghai N Timestamp normal UPDATED_TIME 0 -1 表输入 UPDATED_TIME . , none N Y 0 N N N zh_CN Asia/Shanghai N 160 272 Y 表输出 TableOutput Y 1 none epdc_analysis_target ${esua.epdc.analysis.database}
epdc_dept_event_person_time
500 N N Y N N N Y N Y N 768 272 Y N