我在进行Mybatis调试时出现了下面的警告提示: Generation Warnings Occured Table configuration with catalog null, schema...null, and table 表名 did not resolve to any tables Mybatis generator操作没有产生结果。
, typeFactory, schema); pushGeneratedProjection(context, relBuilder, schema); }...schema.getWatermarkSpecs().isEmpty()) { pushWatermarkAssigner(context, relBuilder, schema...catalog, //GenericlnMemoryCatalog ObjectIdentifier objectIdentifier,//`default_catalog`....`orders` CatalogTable catalogTable,//CatalogTableImpl ReadableConfig configuration...new DefaultDynamicTableContext( objectIdentifier, catalogTable, configuration
[WARNING] Table configuration with catalog null, schema null, and table shop_users did not resolve to...nullCatalogMeansCurrent 字面意思很简单,就是说如果是null catalog,我就选择current.因为mysql不支持catalog,我们需要告知mybatis这个特性,设置为...按照SQL标准的解释,在SQL环境下Catalog和Schema都属于抽象概念,主要用来解决命名冲突问题。...从概念上说,一个数据库系统包含多个Catalog,每个Catalog又包含多个Schema,而每个Schema又包含多个数据库对象(表、视图、序列等),反过来讲一个数据库对象必然属于一个Schema,而该...Schema又必然属于一个Catalog,这样我们就可以得到该数据库对象的完全限定名称从而解决命名冲突的问题了 从实现的角度来看,各种数据库系统对Catalog和Schema的支持和实现方式千差万别,
Created by Jerry Wang, last modified on Jun 16, 2014 创建一个新的database table: [外链图片转存失败(img-POrfREjo-1562208997884
问题描述 今天在读取表的注释信息(COMMENT)时,发现返回的REMARKS字段返回居然是null....DatabaseMetaData meta = this.pConnection.getMetaData(); // 获取所有表信息 ResultSet resultSet = this.meta.getTables(this.catalog..., tableSchema, pattern, this.tableTypes); while (resultSet.next()) { Table table = new Table();...# 返回null String comment=resultSet.getString("REMARKS"); } resultSet.close(); 原因分析 google找了半天,总算知道原因...》 《Retrieve mysql table comment using DatabaseMetaData》 《Chapter 24 INFORMATION_SCHEMA Tables》
", "dbName", "tableName") scan操作用于从schema读取指定的table,也可以传入catalogName及dbName从指定的catalog及db读取 TableEnvironment.scan...= null) { val tableName = tablePath(tablePath.length - 1) val table = schema.getTable(tableName...= null) { return Some(new Table(this, CatalogNode(tablePath, table.getRowType(typeFactory))))...if (schema == null) { return schema } } schema } //...... } scan方法内部调用的是scanInternal...方法查找Table 小结 TableEnvironment的scan操作就是从Schema中查找Table,可以使用tableName,或者额外指定catalog及db来查找 getSchema是使用SchemaPlus
val tab: Table = tableEnv.scan("tableName") //Scanning a table from a registered catalog val tab:...= null) { val tableName = tablePath(tablePath.length - 1) val table = schema.getTable(tableName...= null) { return Some(new Table(this, CatalogNode(tablePath, table.getRowType(typeFactory))))...if (schema == null) { return schema } } schema } //...... } scan方法内部调用的是scanInternal...方法查找Table 小结 TableEnvironment的scan操作就是从Schema中查找Table,可以使用tableName,或者额外指定catalog及db来查找 getSchema是使用SchemaPlus
this.database : schema; } return catalog == null && this.nullDatabaseMeansCurrent.getValue...this.database : catalog; } 这个时候就看到了schema和catelog的都是null,然后继续跟下去的话sql就变成了如下 SELECT TABLE_SCHEMA AS...TABLE_CAT, NULL AS TABLE_SCHEM, TABLE_NAME, CASE WHEN TABLE_TYPE='BASE TABLE' THEN CASE WHEN TABLE_SCHEMA...= 'mysql' OR TABLE_SCHEMA = 'performance_schema' THEN 'SYSTEM TABLE' ELSE 'TABLE' END WHEN TABLE_TYPE...',null,null,null,null) ORDER BY TABLE_TYPE, TABLE_SCHEMA, TABLE_NAME 根据这个sql执行的结果可以看到我的数据库中是存在数据的 学习笔记
配置和表的Schema,方便后续向路径写数据时可以找到对应的表 Configuration hadoopConf = new Configuration(); Catalog...table = null; // 通过catalog判断表是否存在,不存在就创建,存在就加载 if (!...catalog.tableExists(name)) { table = catalog.createTable(name, schema, spec, props);...在向Iceberg表中写数据之前需要创建对应的Catalog、表Schema,否则写出时只指定对应的路径会报错找不到对应的Iceberg表。...hadoopConf = new Configuration(); //2.创建Hadoop配置、Catalog配置和表的Schema,方便后续向路径写数据时可以找到对应的表
********* TABLE_CATALOG: def TABLE_SCHEMA: test TABLE_NAME: test_tab TABLE_TYPE: BASE...**************** TABLE_CATALOG: def TABLE_SCHEMA: test TABLE_NAME: test_tab TABLE_TYPE...**************** TABLE_CATALOG: def TABLE_SCHEMA: test TABLE_NAME: test_tab TABLE_TYPE...**************** TABLE_CATALOG: def TABLE_SCHEMA: test TABLE_NAME: test_tab TABLE_TYPE...**************** TABLE_CATALOG: def TABLE_SCHEMA: test TABLE_NAME: test_tab TABLE_TYPE
bigint PRIMARY KEY NOT NULL AUTO_INCREMENT COMMENT '项目ID',-- database id `catalog_name` varchar(...-- 创建表的 sql create table table_info ( `id` bigint PRIMARY KEY NOT NULL AUTO_INCREMENT,...table properties_info ( `id` bigint PRIMARY KEY NOT NULL AUTO_INCREMENT , `table_id` bigint...schema.0.name=id, schema.0.data-type=INT NOT NULL, schema.1.name=name, schema.1.data-type=VARCHAR...(2147483647) schema.2.name=age, schema.2.data-type=BIGINT, schema.primary-key.name=PK_3386, schema.primary-key.columns
3.2 查看表的字段的信息 select table_schema||'.'...||table_name as tablename,column_name,case character_maximum_length is null when 't' then data_typeelse...where table_schema='schema'and table_name='tablename';schema : schema的信息Tablename : 表的名字 3.3 查看schema...||table_name as tablename,column_name,case character_maximum_length is null when 't' then data_typeelse...where table_schema='schema'and table_name='tablename';schema :schem信息tablename : 表的名字 3.9 查看表字段的注释信息
*********************** TABLE_CATALOG: def TABLE_SCHEMA: sbtest TABLE_NAME: sbtest1...CONSTRAINT_NAME: PRIMARY TABLE_CATALOG: def TABLE_SCHEMA: sbtest...:约束名称 TABLE_CATALOG:约束所在的表的登记名称,该列值总是为def TABLE_SCHEMA:约束所在的数据库名 TABLE_NAME:约束所在的表名 COLUMN_NAME:约束所在的列名...1. row *************************** TABLE_CATALOG: def TABLE_SCHEMA: sbtest TABLE_NAME: sbtest1 NON_UNIQUE...in set (0.00 sec) 字段含义如下(部分字段) TABLE_CATALOG:该字段总是为def TABLE_SCHEMA:表示索引对应的表所属的数据库名称 TABLE_NAME:表示索引所属的表名
数据库,输入如下指令: -- 方法4 SELECT * FROM information_schema.COLUMNS WHERE table_schema = 'employees' AND table_name...departments'; 查询结果如下: mysql> SELECT * -> FROM information_schema.COLUMNS -> WHERE table_schema...********* TABLE_CATALOG: def TABLE_SCHEMA: employees TABLE_NAME:... GENERATION_EXPRESSION: *************************** 2. row *************************** TABLE_CATALOG...: def TABLE_SCHEMA: employees TABLE_NAME: departments COLUMN_NAME
null值 SET ‘table.exec.sink.not-null-enforcer’ = ‘DROP’; ALTER TABLE test_null MODIFY coupon_info FLOAT...2.6.2 模式表 Schemas Table 通过schemas表可以查询该表的历史schema。...其schema将从所有指定的 MySQL 表派生。如果 Paimon 表已存在,则其schema将与所有指定 MySQL 表的schema进行比较。...其schema将从所有指定的 MySQL 表派生。如果 Paimon 表已存在,则其schema将与所有指定 MySQL 表的schema进行比较。...=input \ –table-conf sink.parallelism=4 2.8.3 支持的schema变更 cdc 集成支持有限的schema变更。
问题描述 在hudi 0.12.0版本,flink和spark都可以基于hive metastore进行元数据管理,更多信息可参考:hudi HMS Catalog指南。...也就是说基于hudi hms catalog,flink建表之后,flink或者spark都可以写,或者spark建表之后,spark或者flink都可以写。...但是目前 hudi 0.12.0版本中存在一个问题,当使用flink hms catalog建hudi表之后,spark sql结合spark hms catalog将hive数据进行批量导入时存在无法导入的情况...hadoopConf, Map properties, List partitionKeys) { Schema schema...hadoopConf, Map properties, List partitionKeys) { Schema schema
failed : Column 'IS_REWRITE_ENABLED' cannot accept a NULL value....TBLS" CREATE TABLE "APP"."...TBLS" ("TBL_ID" BIGINT NOT NULL, "CREATE_TIME" INTEGER NOT NULL, "DB_ID" BIGINT, "LAST_ACCESS_TIME" INTEGER...NOT NULL, "OWNER" VARCHAR(767), "RETENTION" INTEGER NOT NULL, "SD_ID" BIGINT, "TBL_NAME" VARCHAR(256.../presto/data sudo chown spuser:spuser -h /var/presto sudo chown spuser:spuser -h /var/presto/data 创建catalog
ubuntu/.dbt/profiles.yml Using dbt_project.yml file at /home/ubuntu/jaffle_shop/dbt_project.yml Configuration...: profiles.yml file [OK found and valid] dbt_project.yml file [OK found and valid] Configuration...| NULL | NULL | NULL | NULL | |...| NULL | NULL | NULL | NULL | |...07:33:59 Catalog written to /home/ubuntu/jaffle_shop/target/catalog.json 开启服务 $ dbt docs serve 07
table_type = 'BASE TABLE' AND table_schema NOT IN ('pg_catalog', 'information_schema'); 2...查看用户建立的VIEW SELECT table_name FROM information_schema.views WHERE table_schema NOT IN ('pg_catalog...', 'information_schema') AND table_name !...information_schema.triggers WHERE trigger_schema NOT IN ('pg_catalog', 'information_schema')...tc LEFT JOIN information_schema.key_column_usage kcu ON tc.constraint_catalog = kcu.constraint_catalog
pg_catalog.pg_size_pretty(pg_catalog.pg_database_size(d.datname)) ELSE 'No Access' END AS..., 'CONNECT') THEN pg_catalog.pg_database_size(d.datname) ELSE NULL END DESC -- nulls... first LIMIT 20 ; 统计数据库中各表占用磁盘大小: SELECT table_schema || '.' || table_name AS table_full_name..., pg_size_pretty(pg_total_relation_size('"' || table_schema || '"."' || table_name || '"')) AS size...FROM information_schema.tables ORDER BY pg_total_relation_size('"' || table_schema || '"."' || table_name
领取专属 10元无门槛券
手把手带您无忧上云