CREATE TABLE public.zy_marketing_plan_relation ( id int8 NOT NULL, plan_id int8 NOT NULL, user_id int8 NOT NULL, user_name varchar(16) NOT NULL, relation_type varchar(16) NOT NULL, is_delete int2 NOT NULL DEFAULT 0, updater varchar(64) NULL DEFAULT ''::character varying, create_time timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, update_time timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, creator varchar(64) NULL DEFAULT ''::character varying ); CREATE TABLE public.zy_marketing_plan ( id bigserial NOT NULL, creator_id int8 NOT NULL, work_type varchar(16) NULL DEFAULT NULL::character varying, start_date date NULL, start_date_detail varchar(2) NULL DEFAULT NULL::character varying, end_date_detail varchar(2) NULL DEFAULT NULL::character varying, customer_id int8 NULL, customer_name varchar(100) NULL DEFAULT NULL::character varying, is_fill_in int2 NOT NULL DEFAULT 0, interviewee varchar(100) NULL DEFAULT NULL::character varying, visit_location varchar(100) NOT NULL, plan_describe varchar(500) NULL DEFAULT NULL::character varying, is_delete int2 NOT NULL DEFAULT 0, updater varchar(64) NULL DEFAULT ''::character varying, create_time timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, update_time timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, visit_purpose varchar(32) NULL DEFAULT NULL::character varying, creator varchar(64) NULL DEFAULT ''::character varying, CONSTRAINT zy_marketing_plan_pkey PRIMARY KEY (id) ); 帮我生成postgresql格式的加表注释和字段注释

时间: 2025-07-25 07:23:31 AIGC 浏览: 21
<think>根据提供的两个表结构,我们需要为每个表以及每个字段添加注释。 在PostgreSQL中,添加注释使用COMMENT命令。 语法: COMMENT ON TABLE table_name IS '表注释'; COMMENT ON COLUMN table_name.column_name IS '字段注释'; 由于问题中没有提供具体的注释内容,我将根据表名和字段名推测其含义并添加注释。 如果实际业务含义不同,请根据实际情况调整注释内容。 表1: zy_marketing_plan_relation (营销计划关系表) 表2: zy_marketing_plan (营销计划表) 接下来,我们为每个表及其字段添加注释。</think>以下是针对您提供的两个 PostgreSQL 表的完整注释脚本,包含表注释和字段注释: ```sql -- 营销计划表注释 COMMENT ON TABLE public.zy_marketing_plan IS '营销计划主表'; -- 营销计划表字段注释 COMMENT ON COLUMN public.zy_marketing_plan.id IS '主键ID'; COMMENT ON COLUMN public.zy_marketing_plan.creator_id IS '创建人ID'; COMMENT ON COLUMN public.zy_marketing_plan.work_type IS '工作类型'; COMMENT ON COLUMN public.zy_marketing_plan.start_date IS '计划开始日期'; COMMENT ON COLUMN public.zy_marketing_plan.start_date_detail IS '开始时间点(如上午/下午)'; COMMENT ON COLUMN public.zy_marketing_plan.end_date_detail IS '结束时间点(如上午/下午)'; COMMENT ON COLUMN public.zy_marketing_plan.customer_id IS '关联客户ID'; COMMENT ON COLUMN public.zy_marketing_plan.customer_name IS '客户名称'; COMMENT ON COLUMN public.zy_marketing_plan.is_fill_in IS '是否已填写报告(0=未填,1=已填)'; COMMENT ON COLUMN public.zy_marketing_plan.interviewee IS '受访人姓名'; COMMENT ON COLUMN public.zy_marketing_plan.visit_location IS '拜访地点'; COMMENT ON COLUMN public.zy_marketing_plan.plan_describe IS '计划描述(500字符限制)'; COMMENT ON COLUMN public.zy_marketing_plan.is_delete IS '逻辑删除标记(0=正常,1=删除)'; COMMENT ON COLUMN public.zy_marketing_plan.updater IS '最后更新人姓名'; COMMENT ON COLUMN public.zy_marketing_plan.create_time IS '创建时间'; COMMENT ON COLUMN public.zy_marketing_plan.update_time IS '最后更新时间'; COMMENT ON COLUMN public.zy_marketing_plan.visit_purpose IS '拜访目的'; COMMENT ON COLUMN public.zy_marketing_plan.creator IS '创建人姓名'; -- 营销计划关系表注释 COMMENT ON TABLE public.zy_marketing_plan_relation IS '营销计划关联人员表'; -- 营销计划关系表字段注释 COMMENT ON COLUMN public.zy_marketing_plan_relation.id IS '主键ID'; COMMENT ON COLUMN public.zy_marketing_plan_relation.plan_id IS '关联营销计划ID'; COMMENT ON COLUMN public.zy_marketing_plan_relation.user_id IS '关联用户ID'; COMMENT ON COLUMN public.zy_marketing_plan_relation.user_name IS '关联用户姓名'; COMMENT ON COLUMN public.zy_marketing_plan_relation.relation_type IS '关联类型(如负责人/参与者)'; COMMENT ON COLUMN public.zy_marketing_plan_relation.is_delete IS '逻辑删除标记(0=正常,1=删除)'; COMMENT ON COLUMN public.zy_marketing_plan_relation.updater IS '最后更新人姓名'; COMMENT ON COLUMN public.zy_marketing_plan_relation.create_time IS '创建时间'; COMMENT ON COLUMN public.zy_marketing_plan_relation.update_time IS '最后更新时间'; COMMENT ON COLUMN public.zy_marketing_plan_relation.creator IS '创建人姓名'; ``` ### 关键说明: 1. **逻辑设计**: - `zy_marketing_plan` 作为主表存储计划核心信息 - `zy_marketing_plan_relation` 作为关联表存储参与人员信息 - 通过 `plan_id` 字段建立两表关联 2. **特殊字段处理**: - `is_delete` 使用 `int2`(相当于SMALLINT)作为布尔标志 - `create_time/update_time` 自动记录时间戳 - `varchar` 长度根据业务场景设定(如用户名16字符,地点100字符) 3. **命名规范**: - 表名使用 `zy_` 前缀表示业务模块 - 字段名采用 `snake_case` 命名法 - 时间字段统一使用 `_time` 后缀 4. **执行说明**: - 需使用超级用户或表所有者账号执行 - 注释会持久化存储在系统目录 `pg_description` 中 - 可通过 `\d+ table_name` 在 psql 中查看注释
阅读全文

相关推荐

优化一下以下sql CREATE TABLE public.zy_marketing_plan ( id bigserial NOT NULL, creator_id int8 NOT NULL, work_type varchar(16) NOT NULL, start_date date NOT NULL, start_date_detail varchar(2) NOT NULL, end_date date NOT NULL, end_date_detail varchar(2) NOT NULL, customer_name varchar(100) NOT NULL, is_fill_in int2 NOT NULL DEFAULT 0, interviewee varchar(100) NULL DEFAULT NULL::character varying, visit_location varchar(100) NOT NULL, describe varchar(500) NULL DEFAULT NULL::character varying, record_id int8 NULL DEFAULT NULL, check_in_id int8 NULL DEFAULT NULL, is_delete int2 NOT NULL DEFAULT 0, created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, CONSTRAINT zy_marketing_plan_pkey PRIMARY KEY (id) ); CREATE INDEX idx_creator_id ON public.zy_marketing_plan USING btree (creator_id); CREATE INDEX idx_start_date ON public.zy_marketing_plan USING btree (start_date); CREATE INDEX idx_end_date ON public.zy_marketing_plan USING btree (end_date); CREATE INDEX idx_record_id ON public.zy_marketing_plan USING btree (record_id); CREATE INDEX idx_check_in_id ON public.zy_marketing_plan USING btree (check_in_id); CREATE TABLE public.zy_marketing_plan_relation ( id bigserial NOT NULL, plan_id int8 NOT NULL, user_id int8 NOT NULL, user_name varchar(16) NOT NULL, relation_type varchar(16) NOT NULL, is_delete int2 NOT NULL DEFAULT 0, created_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, updated_at timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP, CONSTRAINT zy_marketing_plan_relation PRIMARY KEY (id) ); CREATE INDEX idx_plan_id ON public.zy_marketing_plan_relation USING btree (plan_id); CREATE INDEX idx_user_id ON public.zy_marketing_plan_relation USING btree (user_id);

SQL优化以下语句(select f.file_name,a.content_id,c.fd_objectid level_id,c.level level_val,e.fd_objectid manage_id, ifnull((select count(fd_objectid) from message_receiver where MESSAGE_ID = e.fd_objectid), 0) SEND_PEOPLE_NUM, ifnull((select sum(case when reply_content is not null and reply_content != '' then 1 else 0 end) from message_receiver where MESSAGE_ID = e.fd_objectid), 0) reply_num, ifnull((select count(fd_objectid) from (select * from (select *,row_number() over(partition by seq,sendee_tel order by call_stat desc) flag from GROUPCALL_DETAILS) where flag = '1') where busi_id like concat('%', a.content_id) and busi_id like concat(a.event_id, '%')), 0) call_all, ifnull((select sum(case when call_stat like '%0%' then 1 else 0 end) from (select * from (select *,row_number() over(partition by seq,sendee_tel order by call_stat desc) flag from GROUPCALL_DETAILS) where flag = '1') where busi_id like concat('%', a.content_id) and busi_id like concat(a.event_id, '%')), 0) call_jt from NWYJ_SERVICE.ECM_EMYA_ORDER a left join MAP_EMEC_PLAN_CONTENT b on b.FD_OBJECTID = a.CONTENT_ID left join MAP_EMEC_PLAN c on c.FD_OBJECTID = b.RELATION_ID left join MAP_EMEC_ORG_RELATION d on d.FD_OBJECTID = b.ORG_RELATION_ID left join MESSAGE_MANAGE e on e.BUSI_ID = a.FD_OBJECTID left join MAP_EMEC_PLAN_ORG_TREE f on f.fd_objectid = d.org_id where a.event_id = #{eventId} and a.is_del = '0' and b.is_del = '0' and c.is_del = '0' and d.is_del = '0' and f.is_del = '0' and c.fd_objectid = #{levelId} and e.fd_objectid is not null)

WITH purNo AS ( SELECT T .pinv_id, STRING_AGG ( DISTINCT T.NO, ',' ) AS nos FROM ( SELECT A .pinv_id, C.psm_no AS NO FROM pay_ginv_row A INNER JOIN pur_psm C ON A.psm_id = C.psm_id AND C.del_flag = FALSE WHERE A.del_flag = FALSE AND A.psm_id IS NOT NULL UNION ALL SELECT A .pinv_id, C.psp_no AS NO FROM pay_ginv_row A INNER JOIN pur_psp C ON A.psp_id = C.psp_id AND C.del_flag = FALSE WHERE A.del_flag = FALSE AND A.psp_id IS NOT NULL ) T GROUP BY T.pinv_id ), invoiceNos AS ( SELECT pinv_id, STRING_AGG ( INVOICE_NO, ',' ORDER BY INVOICE_NO ) AS invoiceNos FROM PAY_PINV_INV WHERE DEL_FLAG = FALSE GROUP BY pinv_id ) SELECT payPinv.*, basCurr.CURR_NAME_CN currNameCn, basCurr.CURR_NAME_EN currNameEn, payPinv.BU_NAME AS buNames, payPinv.BU_ID AS buIds, payPinv.BD_NAME AS bdNames, payPinv.BD_ID AS bdIds, payPinv.PU_NAME AS puNames, payPinv.PU_ID AS puIds, purNo.nos AS psmNo, COALESCE ( invoiceNos.invoiceNos, '' ) AS invoiceNos FROM PAY_PINV payPinv LEFT JOIN BAS_CURR basCurr ON basCurr.CURR_ID = payPinv.CURR_ID AND basCurr.del_flag = FALSE LEFT JOIN purNo ON purNo.pinv_id = payPinv.pinv_id LEFT JOIN invoiceNos ON invoiceNos.pinv_id = payPinv.pinv_id WHERE payPinv.DEL_FLAG = FALSE AND ( payPinv.CRT_USER_ID ='f5785a75b1044364a08b50c934f05831' OR ( 1 = 1 AND ( 1 = 1 ) ) ) AND payPinv.BILL_TYPE_CODE = 'GINV ' AND to_char( '2025-03-08', 'yyyy-mm-dd' ) <= to_char( payPinv.CRT_TIME, 'yyyy-mm-dd' ) AND to_char( '2025-09-08', 'yyyy-mm-dd' ) >= to_char( payPinv.CRT_TIME, 'yyyy-mm-dd' ) AND ( CASE WHEN payPinv.TRADE_FLAG THEN '1' WHEN payPinv.TRADE_FLAG IS NULL THEN NULL ELSE'0' END ) IN ( '0' , '1' ) ORDER BY payPinv.CRT_TIME DESC > ERROR: relation "pay_ginv_row" does not exist LINE 11: pay_ginv_row

优化全表扫描 AC_PAYMENT_ACCOUNT 根本原因:缺少有效过滤条件或索引支持。 解决方案: 优化高开销索引扫描 TR_TRADE_BUSINESS_IX6 根本原因:索引选择率低(返回60K行),回表代价高。 解决方案: 3. 优化嵌套循环连接(NESTED LOOPS OUTER) 根本原因:多次嵌套循环(出现6层)导致复杂度激增。 解决方案: SELECT (‘01’ || tc.trade_confirm_id) AS rs_id, tc.workday AS workday, NULL AS subcenter, ta.name AS trade_account_name, tc.trade_account_no AS trade_account_no, tc.trust_channel_id AS trust_channel_id, tc.ta_account_no AS ta_account_no, tc.fund_code AS fund_code, tc.confirm_amount AS amount, ‘01’ AS accrual_id, NULL AS investor_bank_code, NULL AS investor_bank_acco_name, NULL AS investor_bank_acco_bank_branch, NULL AS investor_bank_acco_no, (CASE WHEN cr.capital_channel_id = ‘5’ THEN SUBSTR(v.bis_serial_no, 7) WHEN cr.capital_channel_id = ‘2’ THEN SUBSTR(v.bis_serial_no, 6) ELSE v.bis_serial_no END) AS request_serial_no, ‘156’ AS currency, tr.station_id AS station_id, (CASE WHEN tr.business_type = ‘T422’ THEN (CASE (SELECT pd.type FROM pd_fund pd WHERE pd.fund_code = tr.target_fund_code) WHEN ‘10’ THEN NVL(tc.return_channel_id, ‘8’) ELSE ‘y’ END) WHEN tc.return_channel_id in (‘7a’, ‘8a’) THEN NVL(tb.return_channel_id, pc.pay_channel_id) ELSE NVL(tc.return_channel_id, pc.pay_channel_id) END) AS ccs_capital_method, ca.bank_branch_code AS bank_firm_no, NULL AS seller_account_id, v.business_time AS business_time, (SELECT t.target_value FROM fw_map t WHERE t.map_group = ‘CUSTOMER_TYPE_OTS_CCS’ AND t.source_value = ta.customer_type_id) AS customer_type_id, NULL AS business_aided_code, NULL AS remit_status, v.bank_serial_no AS opposite_serial_no, tc.target_fund_code AS opposite_fund_code, NULL AS source_request_capital_method, tc.confirm_no AS keep_field, TO_DATE(‘2025-09-03’, ‘YYYY-MM-DD’) AS exec_workday, tc.confirm_no AS ta_confirm_no, NULL AS IS_TRANSFERED, NULL AS CCS_ACCOUNT_ID, NULL AS TRADE_BUSINESS_TIME, TC.TA_CODE AS TA_CODE, NULL AS ta_confirm_code, TO_CHAR(tc.buy_transfer_date, ‘yyyyMMdd’) AS loan_date, ‘02’ AS batch_no, tc.trade_request_id AS application_sheet_id, (CASE WHEN tr.business_type = ‘TI22’ THEN tr.source_request_id ELSE tr.trade_request_id END) AS request_group_id FROM (SELECT TTB.TRADE_BUSINESS_ID TRADE_CONFIRM_ID, ‘T’ || TTB.BUSINESS_TYPE BUSINESS_TYPE, TTB.TRADE_REQUEST_ID TRADE_REQUEST_ID, TTB.CONFIRM_NO CONFIRM_NO, TTB.TA_ACCOUNT_NO TA_ACCOUNT_NO, TTB.TRADE_ACCOUNT_NO TRADE_ACCOUNT_NO, TTB.TRUST_CHANNEL_ID TRUST_CHANNEL_ID, TTB.PAYMENT_CHANNEL_ID, TTB.FUND_CODE FUND_CODE, TTB.CONFIRM_STATE CONFIRM_STATE, TTB.APPLICATION_AMOUNT APPLICATION_AMOUNT, TTB.CONFIRM_AMOUNT CONFIRM_AMOUNT, TTB.CONFIRM_INTEREST CONFIRM_INTEREST, TTB.TRANSFER_AMOUNT, TTB.WORKDAY WORKDAY, TTB.RETURN_CHANNEL_ID RETURN_CHANNEL_ID, TTB.RETURN_CHANNEL_ACCOUNT_NO RETURN_CHANNEL_ACCOUNT_NO, TTB.TA_CODE TA_CODE, TTB.REDEEM_CAPITAL_RECEIVE_DAYS REDEEM_CAPITAL_RECEIVE_DAYS, TTB.BUY_CONFIRM_RETURN_DAYS BUY_CONFIRM_RETURN_DAYS, TTB.BUY_TRANSFER_DATE BUY_TRANSFER_DATE, TTB.TARGET_FUND_CODE TARGET_FUND_CODE, TTB.REQUEST_GROUP_ID REQUEST_GROUP_ID FROM TR_TRADE_BUSINESS TTB WHERE TTB.BUSINESS_CATEGORY = ‘30’ AND TTB.BUSINESS_TYPE <> ‘143’ AND TTB.WORKDAY >= TO_DATE(‘2025-09-03’, ‘YYYY-MM-DD’) AND TTB.WORKDAY < TO_DATE(‘2025-09-03’, ‘YYYY-MM-DD’) + 1 AND (TTB.TA_CODE = ‘02’ or TTB.TA_CODE = ‘04’ or TTB.TA_CODE = ‘05’ or TTB.TA_CODE = ‘06’ or TTB.TA_CODE = ‘08’ or TTB.TA_CODE = ‘09’ or TTB.TA_CODE = ‘0A’ or TTB.TA_CODE = ‘0F’ or TTB.TA_CODE = ‘0Q’ or TTB.TA_CODE = ‘0W’ or TTB.TA_CODE = ‘0Z’ or TTB.TA_CODE = ‘12’ or TTB.TA_CODE = ‘15’ or TTB.TA_CODE = ‘16’ or TTB.TA_CODE = ‘17’ or TTB.TA_CODE = ‘1L’ or TTB.TA_CODE = ‘1M’ or TTB.TA_CODE = ‘1N’ or TTB.TA_CODE = ‘20’ or TTB.TA_CODE = ‘21’ or TTB.TA_CODE = ‘23’ or TTB.TA_CODE = ‘25’ or TTB.TA_CODE = ‘27’ or TTB.TA_CODE = ‘29’ or TTB.TA_CODE = ‘2E’ or TTB.TA_CODE = ‘30’ or TTB.TA_CODE = ‘32’ or TTB.TA_CODE = ‘33’ or TTB.TA_CODE = ‘34’ or TTB.TA_CODE = ‘36’ or TTB.TA_CODE = ‘37’ or TTB.TA_CODE = ‘39’ or TTB.TA_CODE = ‘3J’ or TTB.TA_CODE = ‘3K’ or TTB.TA_CODE = ‘3M’ or TTB.TA_CODE = ‘3Q’ or TTB.TA_CODE = ‘3Z’ or TTB.TA_CODE = ‘40’ or TTB.TA_CODE = ‘42’ or TTB.TA_CODE = ‘46’ or TTB.TA_CODE = ‘47’ or TTB.TA_CODE = ‘49’ or TTB.TA_CODE = ‘4C’ or TTB.TA_CODE = ‘4T’ or TTB.TA_CODE = ‘4U’ or TTB.TA_CODE = ‘4Z’ or TTB.TA_CODE = ‘53’ or TTB.TA_CODE = ‘55’ or TTB.TA_CODE = ‘57’ or TTB.TA_CODE = ‘58’ or TTB.TA_CODE = ‘5C’ or TTB.TA_CODE = ‘5D’ or TTB.TA_CODE = ‘5L’ or TTB.TA_CODE = ‘5R’ or TTB.TA_CODE = ‘60’ or TTB.TA_CODE = ‘62’ or TTB.TA_CODE = ‘63’ or TTB.TA_CODE = ‘67’ or TTB.TA_CODE = ‘69’ or TTB.TA_CODE = ‘6E’ or TTB.TA_CODE = ‘6F’ or TTB.TA_CODE = ‘6K’ or TTB.TA_CODE = ‘70’ or TTB.TA_CODE = ‘74’ or TTB.TA_CODE = ‘75’ or TTB.TA_CODE = ‘76’ or TTB.TA_CODE = ‘7B’ or TTB.TA_CODE = ‘81’ or TTB.TA_CODE = ‘94’ or TTB.TA_CODE = ‘95’ or TTB.TA_CODE = ‘B0’ or TTB.TA_CODE = ‘C4’ or TTB.TA_CODE = ‘CJ’ or TTB.TA_CODE = ‘H0’ or TTB.TA_CODE = ‘SP’ or TTB.TA_CODE = ‘B6’ or TTB.TA_CODE = ‘0’)) tc LEFT JOIN tr_trade_business tb ON tc.trade_request_id = tb.trade_business_id LEFT JOIN tr_business_relation br ON br.atom_business_id = tc.trade_request_id LEFT JOIN tr_trade_request tr ON tr.trade_request_id = br.business_id LEFT JOIN ac_trade_account ta ON ta.trade_account_no = tc.trade_account_no LEFT JOIN ac_return_account_latest cu ON tc.trade_account_no = cu.trade_account_no AND tc.PAYMENT_CHANNEL_ID = cu.trust_channel_id LEFT JOIN ac_current_account ca ON cu.current_account_id = ca.current_account_id LEFT JOIN ac_payment_channel pc ON pc.payment_channel_id = tc.PAYMENT_CHANNEL_ID LEFT JOIN ca_voucher v ON v.trade_request_id = tc.trade_request_id LEFT JOIN ca_channel_relation cr ON cr.channel_relation_id = v.channel_relation_id WHERE (tc.business_type = ‘T122’ OR tc.business_type = ‘T139’ OR tc.business_type = ‘T191’) AND tc.confirm_amount <> 0 AND tc.workday >= TO_DATE(‘2025-09-03’, ‘YYYY-MM-DD’) AND tc.workday < TO_DATE(‘2025-09-03’, ‘YYYY-MM-DD’) + 1 这个是原始的sql,请根据优化方案给出调整后的sql

请根据下方sql和执行计划结果,根据执行计划分析优化一下sql的查询效率并给出最终优化后的查询sql SELECT ('01' || tc.trade_confirm_id) AS rs_id, tc.workday AS workday, NULL AS subcenter, ta.name AS trade_account_name, tc.trade_account_no AS trade_account_no, tc.trust_channel_id AS trust_channel_id, tc.ta_account_no AS ta_account_no, tc.fund_code AS fund_code, tc.confirm_amount AS amount, '01' AS accrual_id, NULL AS investor_bank_code, NULL AS investor_bank_acco_name, NULL AS investor_bank_acco_bank_branch, NULL AS investor_bank_acco_no, (CASE WHEN cr.capital_channel_id = '5' THEN SUBSTR(v.bis_serial_no, 7) WHEN cr.capital_channel_id = '2' THEN SUBSTR(v.bis_serial_no, 6) ELSE v.bis_serial_no END) AS request_serial_no, '156' AS currency, tr.station_id AS station_id, (CASE WHEN tr.business_type = 'T422' THEN (CASE (SELECT pd.type FROM pd_fund pd WHERE pd.fund_code = tr.target_fund_code) WHEN '10' THEN NVL(tc.return_channel_id, '8') ELSE 'y' END) WHEN tc.return_channel_id in ('7a', '8a') THEN NVL(tb.return_channel_id, pc.pay_channel_id) ELSE NVL(tc.return_channel_id, pc.pay_channel_id) END) AS ccs_capital_method, ca.bank_branch_code AS bank_firm_no, NULL AS seller_account_id, v.business_time AS business_time, (SELECT t.target_value FROM fw_map t WHERE t.map_group = 'CUSTOMER_TYPE_OTS_CCS' AND t.source_value = ta.customer_type_id) AS customer_type_id, NULL AS business_aided_code, NULL AS remit_status, v.bank_serial_no AS opposite_serial_no, tc.target_fund_code AS opposite_fund_code, NULL AS source_request_capital_method, tc.confirm_no AS keep_field, TO_DATE('2025-09-03', 'YYYY-MM-DD') AS exec_workday, tc.confirm_no AS ta_confirm_no, NULL AS IS_TRANSFERED, NULL AS CCS_ACCOUNT_ID, NULL AS TRADE_BUSINESS_TIME, TC.TA_CODE AS TA_CODE, NULL AS ta_confirm_code, TO_CHAR(tc.buy_transfer_date, 'yyyyMMdd') AS loan_date, '02' AS batch_no, tc.trade_request_id AS application_sheet_id, (CASE WHEN tr.business_type = 'TI22' THEN tr.source_request_id ELSE tr.trade_request_id END) AS request_group_id FROM (SELECT TTB.TRADE_BUSINESS_ID TRADE_CONFIRM_ID, 'T' || TTB.BUSINESS_TYPE BUSINESS_TYPE, TTB.TRADE_REQUEST_ID TRADE_REQUEST_ID, TTB.CONFIRM_NO CONFIRM_NO, TTB.TA_ACCOUNT_NO TA_ACCOUNT_NO, TTB.TRADE_ACCOUNT_NO TRADE_ACCOUNT_NO, TTB.TRUST_CHANNEL_ID TRUST_CHANNEL_ID, TTB.PAYMENT_CHANNEL_ID, TTB.FUND_CODE FUND_CODE, TTB.CONFIRM_STATE CONFIRM_STATE, TTB.APPLICATION_AMOUNT APPLICATION_AMOUNT, TTB.CONFIRM_AMOUNT CONFIRM_AMOUNT, TTB.CONFIRM_INTEREST CONFIRM_INTEREST, TTB.TRANSFER_AMOUNT, TTB.WORKDAY WORKDAY, TTB.RETURN_CHANNEL_ID RETURN_CHANNEL_ID, TTB.RETURN_CHANNEL_ACCOUNT_NO RETURN_CHANNEL_ACCOUNT_NO, TTB.TA_CODE TA_CODE, TTB.REDEEM_CAPITAL_RECEIVE_DAYS REDEEM_CAPITAL_RECEIVE_DAYS, TTB.BUY_CONFIRM_RETURN_DAYS BUY_CONFIRM_RETURN_DAYS, TTB.BUY_TRANSFER_DATE BUY_TRANSFER_DATE, TTB.TARGET_FUND_CODE TARGET_FUND_CODE, TTB.REQUEST_GROUP_ID REQUEST_GROUP_ID FROM TR_TRADE_BUSINESS TTB WHERE TTB.BUSINESS_CATEGORY = '30' AND TTB.BUSINESS_TYPE <> '143' AND TTB.WORKDAY >= TO_DATE('2025-09-03', 'YYYY-MM-DD') AND TTB.WORKDAY < TO_DATE('2025-09-03', 'YYYY-MM-DD') + 1 AND (TTB.TA_CODE = '02' or TTB.TA_CODE = '04' or TTB.TA_CODE = '05' or TTB.TA_CODE = '06' or TTB.TA_CODE = '08' or TTB.TA_CODE = '09' or TTB.TA_CODE = '0A' or TTB.TA_CODE = '0F' or TTB.TA_CODE = '0Q' or TTB.TA_CODE = '0W' or TTB.TA_CODE = '0Z' or TTB.TA_CODE = '12' or TTB.TA_CODE = '15' or TTB.TA_CODE = '16' or TTB.TA_CODE = '17' or TTB.TA_CODE = '1L' or TTB.TA_CODE = '1M' or TTB.TA_CODE = '1N' or TTB.TA_CODE = '20' or TTB.TA_CODE = '21' or TTB.TA_CODE = '23' or TTB.TA_CODE = '25' or TTB.TA_CODE = '27' or TTB.TA_CODE = '29' or TTB.TA_CODE = '2E' or TTB.TA_CODE = '30' or TTB.TA_CODE = '32' or TTB.TA_CODE = '33' or TTB.TA_CODE = '34' or TTB.TA_CODE = '36' or TTB.TA_CODE = '37' or TTB.TA_CODE = '39' or TTB.TA_CODE = '3J' or TTB.TA_CODE = '3K' or TTB.TA_CODE = '3M' or TTB.TA_CODE = '3Q' or TTB.TA_CODE = '3Z' or TTB.TA_CODE = '40' or TTB.TA_CODE = '42' or TTB.TA_CODE = '46' or TTB.TA_CODE = '47' or TTB.TA_CODE = '49' or TTB.TA_CODE = '4C' or TTB.TA_CODE = '4T' or TTB.TA_CODE = '4U' or TTB.TA_CODE = '4Z' or TTB.TA_CODE = '53' or TTB.TA_CODE = '55' or TTB.TA_CODE = '57' or TTB.TA_CODE = '58' or TTB.TA_CODE = '5C' or TTB.TA_CODE = '5D' or TTB.TA_CODE = '5L' or TTB.TA_CODE = '5R' or TTB.TA_CODE = '60' or TTB.TA_CODE = '62' or TTB.TA_CODE = '63' or TTB.TA_CODE = '67' or TTB.TA_CODE = '69' or TTB.TA_CODE = '6E' or TTB.TA_CODE = '6F' or TTB.TA_CODE = '6K' or TTB.TA_CODE = '70' or TTB.TA_CODE = '74' or TTB.TA_CODE = '75' or TTB.TA_CODE = '76' or TTB.TA_CODE = '7B' or TTB.TA_CODE = '81' or TTB.TA_CODE = '94' or TTB.TA_CODE = '95' or TTB.TA_CODE = 'B0' or TTB.TA_CODE = 'C4' or TTB.TA_CODE = 'CJ' or TTB.TA_CODE = 'H0' or TTB.TA_CODE = 'SP' or TTB.TA_CODE = 'B6' or TTB.TA_CODE = '0')) tc LEFT JOIN tr_trade_business tb ON tc.trade_request_id = tb.trade_business_id LEFT JOIN tr_business_relation br ON br.atom_business_id = tc.trade_request_id LEFT JOIN tr_trade_request tr ON tr.trade_request_id = br.business_id LEFT JOIN ac_trade_account ta ON ta.trade_account_no = tc.trade_account_no LEFT JOIN ac_return_account_latest cu ON tc.trade_account_no = cu.trade_account_no AND tc.PAYMENT_CHANNEL_ID = cu.trust_channel_id LEFT JOIN ac_current_account ca ON cu.current_account_id = ca.current_account_id LEFT JOIN ac_payment_channel pc ON pc.payment_channel_id = tc.PAYMENT_CHANNEL_ID LEFT JOIN ca_voucher v ON v.trade_request_id = tc.trade_request_id LEFT JOIN ca_channel_relation cr ON cr.channel_relation_id = v.channel_relation_id WHERE (tc.business_type = 'T122' OR tc.business_type = 'T139' OR tc.business_type = 'T191') AND tc.confirm_amount <> 0 AND tc.workday >= TO_DATE('2025-09-03', 'YYYY-MM-DD') AND tc.workday < TO_DATE('2025-09-03', 'YYYY-MM-DD') + 1 执行计划 Description 对象所有者 对象名称 耗费 基数 字节 SELECT STATEMENT, GOAL = ALL_ROWS 14,906 3 1,413 TABLE ACCESS BY INDEX ROWID WOTS PD_FUND 2 1 10 INDEX UNIQUE SCAN WOTS PK_PD_FUND 1 1 INDEX RANGE SCAN WOTS FW_TRANSLATE_IX1 2 1 33 NESTED LOOPS OUTER 14,906 3 1,413 NESTED LOOPS OUTER 14,897 3 1,326 NESTED LOOPS OUTER 14,891 3 1,134 HASH JOIN OUTER 14,887 3 1,032 NESTED LOOPS OUTER 14,884 3 1,008 NESTED LOOPS OUTER 14,882 3 855 HASH JOIN OUTER 14,879 3 660 NESTED LOOPS OUTER 12,802 3 570 NESTED LOOPS OUTER 12,799 3 507 TABLE ACCESS BY INDEX ROWID WOTS TR_TRADE_BUSINESS 12,798 3 456 INDEX RANGE SCAN WOTS TR_TRADE_BUSINESS_IX6 333 60,843 TABLE ACCESS BY INDEX ROWID WOTS AC_PAYMENT_CHANNEL 1 1 17 INDEX UNIQUE SCAN WOTS PK_AC_PAYMENT_CHANNEL 0 1 INDEX RANGE SCAN WOTS IDX_AC_TRADE_ACCOUNT_2 1 1 21 VIEW WOTS AC_RETURN_ACCOUNT_LATEST 2,077 125,458 3,763,740 NESTED LOOPS OUTER 2,077 125,458 6,649,274 VIEW WOTS 2,062 125,458 5,018,320 WINDOW SORT PUSHED RANK 2,062 125,458 6,649,274 TABLE ACCESS FULL WOTS AC_PAYMENT_ACCOUNT 418 125,458 6,649,274 INDEX UNIQUE SCAN WOTS PK_AC_CURRENT_ACCOUNT 0 1 13 TABLE ACCESS BY INDEX ROWID WOTS AC_CURRENT_ACCOUNT 1 1 65 INDEX UNIQUE SCAN WOTS PK_AC_CURRENT_ACCOUNT 0 1 INDEX RANGE SCAN WOTS IDX_CA_VOUCHER_6 2 1 51 VIEW WOTS index$_join$_021 2 28 224 HASH JOIN INDEX FAST FULL SCAN WOTS IDX_CA_CHANNEL_RELATION_1 1 28 224 INDEX FAST FULL SCAN WOTS PK_CA_CHANNEL_RELATION 1 28 224 TABLE ACCESS BY INDEX ROWID WOTS TR_BUSINESS_RELATION 4 1 34 INDEX RANGE SCAN WOTS IDX_TR_BUSINESS_RELATION_1 3 1 TABLE ACCESS BY INDEX ROWID WOTS TR_TRADE_REQUEST 2 1 64 INDEX UNIQUE SCAN WOTS PK_TR_TRADE_REQUEST 1 1 TABLE ACCESS BY INDEX ROWID WOTS TR_TRADE_BUSINESS 3 1 29 INDEX UNIQUE SCAN WOTS PK_TR_TRADE_BUSINESS 2 1

greenPlum数据库建表语句如下: -- 建schema CREATE SCHEMA schemaname AUTHORIZATION "insight-gp7_vops"; -- 按天分区表 DROP TABLE IF EXISTS pt.vd_process_day_partition; CREATE TABLE pt.vd_process_day_partition ( uuid VARCHAR(256), groupId VARCHAR(256), nodeId VARCHAR(256), vops_insert_time timestamp, createtime timestamp, pid FLOAT, process_name VARCHAR(256), cpu FLOAT, mem FLOAT, handle int, os_type int ) WITH (appendonly=true, orientation=column, compresstype=zlib, compresslevel=5) DISTRIBUTED BY (uuid) PARTITION BY RANGE(createtime) (START ('2025-2-1'::date) END ('2025-5-31'::date) EVERY ('1 day'::interval), DEFAULT PARTITION process_default); COMMENT ON TABLE pt.vd_process_day_partition IS '用户进程资源使用表'; COMMENT ON COLUMN pt.vd_process_day_partition.uuid IS '用户UUID'; COMMENT ON COLUMN pt.vd_process_day_partition.groupId IS '组织 ID'; COMMENT ON COLUMN pt.vd_process_day_partition.nodeId IS '站点 ID'; COMMENT ON COLUMN pt.vd_process_day_partition.vops_insert_time IS 'VOPS Insert Time'; COMMENT ON COLUMN pt.vd_process_day_partition.createtime IS 'Create Time'; COMMENT ON COLUMN pt.vd_process_day_partition.pid IS 'Process ID'; COMMENT ON COLUMN pt.vd_process_day_partition.process_name IS 'Process Name'; COMMENT ON COLUMN pt.vd_process_day_partition.cpu IS 'CPU Usage'; COMMENT ON COLUMN pt.vd_process_day_partition.handle IS '句柄数'; COMMENT ON COLUMN pt.vd_process_day_partition.mem IS 'Memory Usage'; COMMENT ON COLUMN pt.vd_process_day_partition.os_type IS 'OS Type'; 请设计一些常用的插叙语句,比如求和,求平均等

SELECT t.DOCTOR_CODE AS doctorCode, t.DOCTOR_NAME_EN AS doctorNameEn, t.DOCTOR_NAME_CH AS doctorNameCh, spec.subSpecialtyInterestEn, spec.subSpecialtyInterestCh, prov.providerCode, net.networkType, MAX(t.REGION) AS region, CASE WHEN t3.NETWORK_TERMINATION_DATE IS NULL AND t3.NETWORK_CREATION_DATE IS NOT NULL THEN CASE WHEN GETDATE() >= t3.NETWORK_CREATION_DATE THEN 'Y' ELSE 'N' END WHEN t3.NETWORK_CREATION_DATE IS NOT NULL AND t3.NETWORK_TERMINATION_DATE IS NOT NULL THEN CASE WHEN GETDATE() BETWEEN t3.NETWORK_CREATION_DATE AND t3.NETWORK_TERMINATION_DATE THEN 'Y' ELSE 'N' END WHEN t3.NETWORK_CREATION_DATE IS NOT NULL THEN CASE WHEN GETDATE() < t3.NETWORK_TERMINATION_DATE THEN 'N' ELSE 'Y' END ELSE 'N' END AS activeAxaNetwork FROM T_DOCTOR_PROFILE t OUTER APPLY ( SELECT STRING_AGG(SUB_SPECIALTY_INTEREST_EN, ', ') WITHIN GROUP (order by SUB_SPECIALTY_INTEREST_EN), STRING_AGG(SUB_SPECIALTY_INTEREST_CH, ', ') within group ( order by SUB_SPECIALTY_INTEREST_CH ) FROM ( SELECT DISTINCT t2.SUB_SPECIALTY_INTEREST_EN, t2.SUB_SPECIALTY_INTEREST_CH FROM T_DOCTOR_SPECIALTY_INFORMATION t2 WHERE t2.DOCTOR_CODE = t.DOCTOR_CODE AND t2.deleted_flag = '0' ) AS specs ) spec(subSpecialtyInterestEn, subSpecialtyInterestCh) OUTER APPLY ( SELECT STRING_AGG(PROVIDER_CODE, '; ') FROM ( SELECT DISTINCT t3.PROVIDER_CODE FROM T_NETWORK_DOCTOR_PROVIDER_RELATION t3 WHERE t3.DOCTOR_CODE = t.DOCTOR_CODE AND t3.deleted_flag = '0' ) AS provs ) prov(providerCode) OUTER APPLY ( SELECT STRING_AGG(SERVICE_AREA, ', ') FROM ( SELECT DISTINCT t4.SERVICE_AREA FROM T_NETWORK_DOCTOR_PROVIDER_RELATION t3 JOIN T_NETWORK_DOCTOR_PROVIDER t4 ON t3.NETWORK_CODE = t4.NETWORK_CODE WHERE t3.DOCTOR_CODE = t.DOCTOR_CODE AND t3.deleted_flag = '0' AND t4.deleted_flag = '0' ) AS nets ) net(networkType) LEFT JOIN T_NETWORK_DOCTOR_PROVIDER_RELATION t3 ON t3.DOCTOR_CODE = t.DOCTOR_CODE AND t3.deleted_flag = '0' WHERE t.deleted_flag = '0' and t.DOCTOR_CODE = 'DOC001' GROUP BY t.id , t.DOCTOR_CODE, t.DOCTOR_NAME_EN, t.DOCTOR_NAME_CH, spec.subSpecialtyInterestEn, spec.subSpecialtyInterestCh, prov.providerCode, net.networkType, t3.NETWORK_TERMINATION_DATE, t3.NETWORK_CREATION_DATE order by t.id; -- ) -- AS subquery -- WHERE subquery.activeAxaNetwork = 'Y'; 我使用的Sqlserver 数据库版本是2017以上这个sql为什么不能执行

-- THIS SCRIPT IS AUTOMATICALLY GENERATED. DO NOT EDIT IT DIRECTLY. DROP TABLE IF EXISTS mimiciv_derived.sepsis3; CREATE TABLE mimiciv_derived.sepsis3 AS WITH sofa AS ( SELECT stay_id, starttime, endtime, respiration_24hours AS respiration, coagulation_24hours AS coagulation, liver_24hours AS liver, cardiovascular_24hours AS cardiovascular, cns_24hours AS cns, renal_24hours AS renal, sofa_24hours AS sofa_score FROM mimiciv_derived.sofa WHERE sofa_24hours >= 2 ), s1 AS ( SELECT soi.subject_id, soi.stay_id, soi.ab_id, soi.antibiotic, soi.antibiotic_time, soi.culture_time, soi.suspected_infection, soi.suspected_infection_time, soi.specimen, soi.positive_culture, s.starttime, s.endtime, s.respiration, s.coagulation, s.liver, s.cardiovascular, s.cns, s.renal, s.sofa_score, (s.sofa_score >= 2 AND soi.suspected_infection = true) AS sepsis3, ROW_NUMBER() OVER ( PARTITION BY soi.stay_id ORDER BY soi.suspected_infection_time NULLS FIRST, soi.antibiotic_time NULLS FIRST, soi.culture_time NULLS FIRST, s.endtime NULLS FIRST ) AS rn_sus FROM mimiciv_derived.suspicion_of_infection AS soi INNER JOIN sofa AS s ON soi.stay_id = s.stay_id AND s.endtime >= soi.suspected_infection_time - INTERVAL '48 HOUR' AND s.endtime <= soi.suspected_infection_time + INTERVAL '24 HOUR' WHERE soi.stay_id IS NOT NULL ), -- 添加患者基本信息、住院信息和实验室检查 patient_data AS ( SELECT s1.subject_id, s1.stay_id, s1.antibiotic_time, s1.culture_time, s1.suspected_infection_time, s1.endtime AS sofa_time, s1.sofa_score, s1.respiration, s1.coagulation, s1.liver, s1.cardiovascular, s1.cns, s1.renal, s1.sepsis3, p.gender, p.anchor_age, -- 计算住院时长 EXTRACT(EPOCH FROM (ie.outtime - ie.intime))/3600 AS hospital_stay_hours, -- 计算发病至入组时间 EXTRACT(EPOCH FROM (s1.suspected_infection_time - ie.intime))/3600 AS onset_to_admission_hours, -- 获取最近的白蛋白值 FIRST_VALUE(le.valuenum) OVER ( PARTITION BY le.subject_id ORDER BY ABS(EXTRACT(EPOCH FROM (le.charttime - s1.suspected_infection_time))) ) AS albumin_value FROM s1 INNER JOIN mimiciv_hosp.patients p ON s1.subject_id = p.subject_id INNER JOIN mimiciv_icu.icustays ie ON s1.stay_id = ie.stay_id LEFT JOIN mimiciv_hosp.labevents le ON s1.subject_id = le.subject_id AND le.itemid = 50862 -- 白蛋白的项目ID AND le.charttime BETWEEN ie.intime - INTERVAL '24 HOUR' AND ie.intime + INTERVAL '24 HOUR' WHERE s1.rn_sus = 1 AND s1.sepsis3 = true -- 修复这里,使用布尔值true而不是整数1 ), -- 排除标准 exclusion_criteria AS ( SELECT pd.subject_id, pd.stay_id, -- 排除标准判断 MAX(CASE WHEN dx.icd_code LIKE 'O%' OR dx.icd_code IN ('V22.0', 'V23.0', 'V24.0') THEN 1 ELSE 0 END) AS pregnancy_exclude, MAX(CASE WHEN dx.icd_code IN ('K70.2', 'K70.3', 'K70.4', 'K71.7', 'K72.1', 'K72.9', 'K76.7') THEN 1 ELSE 0 END) AS liver_disease_exclude, MAX(CASE WHEN dx.icd_code = 'N18.5' OR dx.icd_code IN ('Z49.0', 'Z49.1', 'Z99.2') THEN 1 ELSE 0 END) AS renal_disease_exclude, MAX(CASE WHEN dx.icd_code LIKE 'F%' OR dx.icd_code IN ('291%', '292%', '293%', '294%', '295%', '296%', '297%', '298%') THEN 1 ELSE 0 END) AS mental_health_exclude FROM patient_data pd LEFT JOIN mimiciv_hosp.diagnoses_icd dx ON pd.subject_id = dx.subject_id GROUP BY pd.subject_id, pd.stay_id ) SELECT pd.*, CASE WHEN ec.pregnancy_exclude = 1 OR ec.liver_disease_exclude = 1 OR ec.renal_disease_exclude = 1 OR ec.mental_health_exclude = 1 THEN true ELSE false END AS excluded, -- 低蛋白血症分组 CASE WHEN pd.albumin_value < 3.5 THEN '低蛋白血症组' ELSE '非低蛋白血症组' END AS albumin_group FROM patient_data pd LEFT JOIN exclusion_criteria ec ON pd.subject_id = ec.subject_id AND pd.stay_id = ec.stay_id WHERE -- 纳入标准 pd.anchor_age >= 18 AND pd.hospital_stay_hours >= 24 AND pd.onset_to_admission_hours <= 24 -- 确保不符合任何排除标准 AND (ec.pregnancy_exclude = 0 AND ec.liver_disease_exclude = 0 AND ec.renal_disease_exclude = 0 AND ec.mental_health_exclude = 0);不能用

最新推荐

recommend-type

autoscaling-jvm-1.5.13.jar

autoscaling-jvm-1.5.13.jar
recommend-type

tempest-testing-2024.04.02.213403-4170185.jar

tempest-testing-2024.04.02.213403-4170185.jar
recommend-type

地搜立刻同意我雄 静电纺丝

给对它的快递费监考老师
recommend-type

exhaustive-annotation-js-0.2.0-javadoc.jar

exhaustive-annotation-js-0.2.0-javadoc.jar
recommend-type

Node.js构建的运动咖啡馆RESTful API介绍

标题《sportscafeold:体育咖啡馆》指出了项目名称为“体育咖啡馆”,这个名字暗示了该项目可能是一个结合了运动和休闲主题的咖啡馆相关的网络服务平台。该项目运用了多种技术栈,核心的开发语言为JavaScript,这从标签中可以得到明确的信息。 从描述中可以提取以下知识点: 1. **Node.js**:体育咖啡馆项目使用了Node.js作为服务器端运行环境。Node.js是一个基于Chrome V8引擎的JavaScript运行环境,它能够使得JavaScript应用于服务器端开发。Node.js的事件驱动、非阻塞I/O模型使其适合处理大量并发连接,这对于RESTFUL API的构建尤为重要。 2. **Express Framework**:项目中使用了Express框架来创建RESTFUL API。Express是基于Node.js平台,快速、灵活且极简的Web应用开发框架。它提供了构建Web和移动应用的强大功能,是目前最流行的Node.js Web应用框架之一。RESTFUL API是一组遵循REST原则的应用架构,其设计宗旨是让Web服务通过HTTP协议进行通信,并且可以使用各种语言和技术实现。 3. **Mongoose ORM**:这个项目利用了Mongoose作为操作MongoDB数据库的接口。Mongoose是一个对象文档映射器(ODM),它为Node.js提供了MongoDB数据库的驱动。通过Mongoose可以定义数据模型,进行数据库操作和查询,从而简化了对MongoDB数据库的操作。 4. **Passport.js**:项目中采用了Passport.js库来实现身份验证系统。Passport是一个灵活的Node.js身份验证中间件,它支持多种验证策略,例如用户名和密码、OAuth等。它提供了标准化的方法来为用户登录提供认证,是用户认证功能的常用解决方案。 5. **版权信息**:项目的版权声明表明了Sportscafe 2015是版权所有者,这表明项目或其相关内容最早发布于2015年或之前。这可能表明该API背后有商业实体的支持或授权使用。 从【压缩包子文件的文件名称列表】中我们可以了解到,该文件的版本控制仓库使用的是“master”分支。在Git版本控制系统中,“master”分支通常用于存放当前可部署的稳定版本代码。在“master”分支上进行的更改通常都是经过测试且准备发布到生产环境的。 综上所述,我们可以知道体育咖啡馆项目是一个利用现代JavaScript技术栈搭建的后端服务。它包含了处理HTTP请求的Express框架、连接MongoDB数据库的Mongoose库和实现用户身份验证的Passport.js中间件。该项目可用于构建提供体育信息、咖啡馆菜单信息、预约服务等的Web应用或API服务,这为体育咖啡馆的营销、用户体验和数据管理提供了可能。 考虑到文档资料的提及,该项目的安装和API文档应该包含在项目资料中,可能在项目的README文件或其他说明文档中。对于项目的使用者或者开发者而言,这部分文档非常重要,因为它们可以提供详细的信息和指导,帮助用户快速部署和使用该API。 总结来说,这是一套针对体育咖啡馆相关业务的后端解决方案,它使用了流行的开源技术栈,可以灵活地应用于体育咖啡馆的网络服务中,如信息发布、在线预约、会员管理等。
recommend-type

【LNR优化与用户体验】:一文看透互操作优化如何提升用户感知

# 摘要 LNR(邻区关系优化)是提升移动通信网络性能与用户体验的关键技术。本文系统阐述了LNR优化的基本概念、理论基础与技术实现路径,构建了包括信道质量评估、干扰建模及关键性能指标分析在内的数学模型,并探讨了参数配置、邻区管理及AI与大数据在LNR优化中的应用。通过量化用户感知指标,分析了LNR优化对视频流畅度、页面加载速度及切换性能的实际改善效果,并结合典型场景验证了其优化成效。本文进一步展望了LNR技术在5G及未来网络中的发展趋势与技术挑战。
recommend-type

Java1.8 的编程语言、使用场景、版本号、厂商、是否开源、发行日期、终止日期、可替代产品、推荐产品是什么

以下是关于 **Java 1.8** 的全面信息汇总,涵盖其编程语言特性、使用场景、版本号、厂商、是否开源、发行日期、终止支持日期、可替代产品和推荐产品。 --- ## ✅ Java 1.8 综合信息表 | 项目 | 内容 | |------|------| | **编程语言** | Java | | **版本号** | Java 1.8(也称为 Java 8) | | **厂商** | Oracle、Adoptium、Amazon(Corretto)、Azul(Zulu)、Red Hat、IBM 等 | | **是否开源** | ✅ 是(OpenJDK 1.8 是开源的,Oracle
recommend-type

Java开发的教区牧民支持系统介绍

根据给定文件信息,下面将详细阐述相关知识点: ### 标题知识点 #### catecumenus-java: 教区牧民支持系统 - **Java技术栈应用**:标题提到的“catecumenus-java”表明这是一个使用Java语言开发的系统。Java是目前最流行的编程语言之一,广泛应用于企业级应用、Web开发、移动应用等,尤其是在需要跨平台运行的应用中。Java被设计为具有尽可能少的实现依赖,所以它可以在多种处理器上运行。 - **教区牧民支持系统**:从标题来看,这个系统可能面向的是教会管理或教区管理,用来支持牧民(教会领导者或牧师)的日常管理工作。具体功能可能包括教友信息管理、教区活动安排、宗教教育资料库、财务管理、教堂资源调配等。 ### 描述知识点 #### 儿茶类 - **儿茶素(Catechin)**:描述中提到的“儿茶类”可能与“catecumenus”(新信徒、教徒)有关联,暗示这个系统可能与教会或宗教教育相关。儿茶素是一类天然的多酚类化合物,常见于茶、巧克力等植物中,具有抗氧化、抗炎等多种生物活性,但在系统标题中可能并无直接关联。 - **系统版本号**:“0.0.1”表示这是一个非常初期的版本,意味着该系统可能刚刚开始开发,功能尚不完善。 ### 标签知识点 #### Java - **Java语言特点**:标签中明确提到了“Java”,这暗示了整个系统都是用Java编程语言开发的。Java的特点包括面向对象、跨平台(即一次编写,到处运行)、安全性、多线程处理能力等。系统使用Java进行开发,可能看重了这些特点,尤其是在构建可扩展、稳定的后台服务。 - **Java应用领域**:Java广泛应用于企业级应用开发中,包括Web应用程序、大型系统后台、桌面应用以及移动应用(Android)。所以,此系统可能也会涉及这些技术层面。 ### 压缩包子文件的文件名称列表知识点 #### catecumenus-java-master - **Git项目结构**:文件名称中的“master”表明了这是Git版本控制系统中的一个主分支。在Git中,“master”分支通常被用作项目的主干,是默认的开发分支,所有开发工作都是基于此分支进行的。 - **项目目录结构**:在Git项目中,“catecumenus-java”文件夹应该包含了系统的源代码、资源文件、构建脚本、文档等。文件夹可能包含各种子文件夹和文件,比如src目录存放Java源代码,lib目录存放相关依赖库,以及可能的build.xml文件用于构建过程(如Ant或Maven构建脚本)。 ### 结合以上信息的知识点整合 综合以上信息,我们可以推断“catecumenus-java: 教区牧民支持系统”是一个使用Java语言开发的系统,可能正处于初级开发阶段。这个系统可能是为了支持教会内部管理,提供信息管理、资源调度等功能。其使用Java语言的目的可能是希望利用Java的多线程处理能力、跨平台特性和强大的企业级应用支持能力,以实现一个稳定和可扩展的系统。项目结构遵循了Git版本控制的规范,并且可能采用了模块化的开发方式,各个功能模块的代码和资源文件都有序地组织在不同的子文件夹内。 该系统可能采取敏捷开发模式,随着版本号的增加,系统功能将逐步完善和丰富。由于是面向教会的内部支持系统,对系统的用户界面友好性、安全性和数据保护可能会有较高的要求。此外,考虑到宗教性质的敏感性,系统的开发和使用可能还需要遵守特定的隐私和法律法规。
recommend-type

LNR切换成功率提升秘籍:参数配置到网络策略的全面指南

# 摘要 LNR(LTE to NR)切换技术是5G网络部署中的关键环节,直接影
recommend-type

How to install watt toolkit in linux ?

安装 Watt Toolkit(原名 Steam++)在 Linux 系统上通常可以通过编译源码或者使用预编译的二进制文件来完成。Watt Toolkit 是一个开源工具,主要用于加速 Steam 平台的下载速度,支持跨平台运行,因此在 Linux 上也能够很好地工作。 ### 安装步骤 #### 方法一:使用预编译的二进制文件 1. 访问 [Watt Toolkit 的 GitHub 仓库](https://github.com/BeyondDimension/SteamTools) 并下载适用于 Linux 的最新版本。 2. 解压下载的压缩包。 3. 给予可执行权限: ```