Merge branch 'apache:master' into ISSUE_31437_WITH_KEYWORD_QUERY_ERRO…

…R_MYSQL

RELEASE-NOTES.md

@@ -141,6 +141,7 @@
 1. Pipeline: Use case-insensitive identifiers to enhance the table metadata loader
 1. Pipeline: Support primary key columns ordering for standard pipeline table metadata loader
 1. Sharding: Optimize sharding table index name rewriting rules and remove unnecessary suffix rewriting - [#31171](https://github.com/apache/shardingsphere/issues/31171)
+1. Metadata: Support postgresql and opengauss CHARACTER VARYING type metadata load - [#34221](https://github.com/apache/shardingsphere/pull/34221)
 
 ### Bug Fixes
 

docs/blog/content/material/2022_03_25_A_Deep_Dive_Into_Observability_Apache_ShardingSphere_Agent.en.md

@@ -199,7 +199,7 @@ After performing the same access test as before, we can view dependencies throug
 
 ## Sampling Rate
 
-The Observability plugin also enables users to set differnt sampling rate configured to suit different scenarios. Zipkin plugins support various sampling rate type configurations including const, counting, rate limiting, and boundary.
+The Observability plugin also enables users to set different sampling rate configured to suit different scenarios. Zipkin plugins support various sampling rate type configurations including const, counting, rate limiting, and boundary.
 
 For scenarios with a high volume of requests, we suggest you to choose the boundary type and configure it with the appropriate sampling rate to reduce the collect volume of tracing data.
 

docs/blog/content/material/2022_04_21_Apache_ShardingSphere_openGauss_Breaking_the_Distributed_Database_Performance_Record_with_10_Million_tpmC.en.md

@@ -64,7 +64,7 @@ This means it can effectively solve problems caused by increasing data volume in
 ## Conclusion
 Apache ShardingSphere and openGauss can seek potential cooperation opportunities.
 
-Considering the increasingly diversified applicaiton scenarios and increasing data volume, the requirements for database performance are at an all time high and will only continue to increase in the future.
+Considering the increasingly diversified application scenarios and increasing data volume, the requirements for database performance are at an all time high and will only continue to increase in the future.
 
 The success of our two communities cooperation is just the beginning of ourtwo communities building a collaborative database ecosystem.
 

docs/blog/content/material/2022_05_10_What’s_the_Database_Plus_concept_and_what_challenges_can_it_solve.en.md

@@ -167,7 +167,7 @@ Apache ShardingSphere currently only supports federated queries between homogene
 ## Conclusion
 The Apache ShardingSphere community has been active in open source for 7 years. Through perseverance, the community has become mature we’d like to extend our sincere welcome to any devs or contributors who are enthusiastic about open source and coding to collaborate with us.
 
-Among our recent achievements we’re particulary proud of, Apache ShardingSphere’s pluggable architecture and data sharding philosophy have been recognized by the academic community. [The paper, Apache ShardingSphere: A Holistic and Pluggable Platform for Data Sharding, has been published at this year’s ICDE, a top conference in the database field.](https://faun.pub/a-holistic-pluggable-platform-for-data-sharding-icde-2022-understanding-apache-shardingsphere-55779cfde16)
+Among our recent achievements we’re particularly proud of, Apache ShardingSphere’s pluggable architecture and data sharding philosophy have been recognized by the academic community. [The paper, Apache ShardingSphere: A Holistic and Pluggable Platform for Data Sharding, has been published at this year’s ICDE, a top conference in the database field.](https://faun.pub/a-holistic-pluggable-platform-for-data-sharding-icde-2022-understanding-apache-shardingsphere-55779cfde16)
 
 ## Author
 

docs/blog/content/material/2022_06_02_Database_Mesh_2.0_Database_Governance_in_a_Cloud_Native_Environment.en.md

@@ -68,7 +68,7 @@ Database Mesh 2.0 focuses on how to achieve the following goals in a cloud nativ
 
 > **Developer experience**
 
-As mentioned above, business developers are mainly concerned about business logic and implementation instead of infrastructure, operation and maintenance features. Developement experience will move towards [Serverless](https://www.redhat.com/en/topics/cloud-native-apps/what-is-serverless), which means it will become more and more transparent and intuitive when accessing databases. Developers only need to understand the type of data storage required by their business, and then use preset or dynamic ID credential information to access corresponding database services.
+As mentioned above, business developers are mainly concerned about business logic and implementation instead of infrastructure, operation and maintenance features. Development experience will move towards [Serverless](https://www.redhat.com/en/topics/cloud-native-apps/what-is-serverless), which means it will become more and more transparent and intuitive when accessing databases. Developers only need to understand the type of data storage required by their business, and then use preset or dynamic ID credential information to access corresponding database services.
 
 > **Programmable**
 

docs/blog/content/material/Jan_28_Full_Link_Online_Stress_Testing_for_Production_Database_Apache_ShardingSphere_Shadow_Database_Feature_Upgrade.en.md

@@ -104,7 +104,7 @@ The data generated from test user order creation will be routed to shadow databa
 
 As mentioned in the introduction, full-link online stress testing is a complicated task that requires collaboration between microservices and middlewares to meet the needs of different traffic and stress testing tag transmissions.
 
-Additonally, the testing service should be stateless and immediately available. [CyborgFlow](https://github.com/SphereEx/CyborgFlow), which is jointly maintained by Apache ShardingSphere, Apache APISIX and Apache SkyWalking provides out-of-the-box (OoTB) solution to run load test in your online system.
+Additionally, the testing service should be stateless and immediately available. [CyborgFlow](https://github.com/SphereEx/CyborgFlow), which is jointly maintained by Apache ShardingSphere, Apache APISIX and Apache SkyWalking provides out-of-the-box (OoTB) solution to run load test in your online system.
 
 [Apache APISIX](https://apisix.apache.org/) is responsible for making tags on testing data at the gateway layer, while [Apache SkyWalking](https://skywalking.apache.org/) is responsible for transmission through the whole scheduling link, and finally, Apache ShardingSphere-Proxy will isolate data and route testing data to the shadow database.
 

docs/blog/content/material/Nov_23_1_Integrate_SCTL_into_RAL.en.md

@@ -189,7 +189,7 @@ Input command
 
 Output
 
-a. If sucessful, show "Query OK, 0 rows affected";
+a. If successful, show "Query OK, 0 rows affected";
 b. Re-execute `show readwrite_splitting hint status`; show the ource is changed into Write;
 c. Execute `preview select * from t_order`and see the queried SQL will go to the master database.
 

docs/document/content/overview/_index.en.md

@@ -65,7 +65,7 @@ ShardingSphere offers a flat learning curve to DBAs and is interaction-friendly
 
 It can provide enhancement capability based on mature databases while ensuring security and stability.
 
-- Elastic Extention
+- Elastic Extension
 
 It supports computing, storage, and smooth online expansion, which can meet diverse business needs.
 

infra/database/type/opengauss/src/main/java/org/apache/shardingsphere/infra/database/opengauss/metadata/database/OpenGaussDatabaseMetaData.java

@@ -64,6 +64,7 @@ public Map<String, Integer> getExtraDataTypes() {
         result.put("NUMERIC", Types.NUMERIC);
         result.put("REAL", Types.REAL);
         result.put("BOOL", Types.BOOLEAN);
+        result.put("CHARACTER VARYING", Types.VARCHAR);
         return result;
     }
 

infra/database/type/postgresql/src/main/java/org/apache/shardingsphere/infra/database/postgresql/metadata/database/PostgreSQLDatabaseMetaData.java

@@ -61,6 +61,7 @@ public Map<String, Integer> getExtraDataTypes() {
         result.put("NUMERIC", Types.NUMERIC);
         result.put("REAL", Types.REAL);
         result.put("BOOL", Types.BOOLEAN);
+        result.put("CHARACTER VARYING", Types.VARCHAR);
         return result;
     }
 

mode/core/src/main/java/org/apache/shardingsphere/mode/metadata/manager/DatabaseRuleConfigurationManager.java

@@ -36,6 +36,7 @@
 import java.util.LinkedList;
 import java.util.Optional;
 import java.util.concurrent.atomic.AtomicReference;
+import java.util.stream.Collectors;
 
 /**
  * Database rule configuration manager.
@@ -74,7 +75,7 @@ public synchronized void alterRuleConfiguration(final String databaseName, final
         rules.removeIf(each -> each.getConfiguration().getClass().isAssignableFrom(ruleConfig.getClass()));
         rules.addAll(DatabaseRulesBuilder.build(
                 databaseName, database.getProtocolType(), database.getRuleMetaData().getRules(), ruleConfig, computeNodeInstanceContext, database.getResourceMetaData()));
-        refreshMetadata(databaseName, database, rules);
+        refreshMetadata(databaseName, getRuleConfigurations(rules));
     }
 
     /**
@@ -98,14 +99,16 @@ public synchronized void dropRuleConfiguration(final String databaseName, final
             rules.addAll(DatabaseRulesBuilder.build(
                     databaseName, database.getProtocolType(), database.getRuleMetaData().getRules(), ruleConfig, computeNodeInstanceContext, database.getResourceMetaData()));
         }
-        refreshMetadata(databaseName, database, rules);
+        refreshMetadata(databaseName, getRuleConfigurations(rules));
     }
 
-    private void refreshMetadata(final String databaseName, final ShardingSphereDatabase database, final Collection<ShardingSphereRule> rules) throws SQLException {
-        database.getRuleMetaData().getRules().clear();
-        database.getRuleMetaData().getRules().addAll(rules);
+    private void refreshMetadata(final String databaseName, final Collection<RuleConfiguration> ruleConfigurations) throws SQLException {
         MetaDataContexts reloadMetaDataContexts = MetaDataContextsFactory.createByAlterRule(databaseName, false,
-                database.getRuleMetaData().getConfigurations(), metaDataContexts.get(), metaDataPersistService, computeNodeInstanceContext);
+                ruleConfigurations, metaDataContexts.get(), metaDataPersistService, computeNodeInstanceContext);
         metaDataContexts.set(reloadMetaDataContexts);
     }
+
+    private Collection<RuleConfiguration> getRuleConfigurations(final Collection<ShardingSphereRule> rules) {
+        return rules.stream().map(ShardingSphereRule::getConfiguration).collect(Collectors.toList());
+    }
 }

mode/core/src/main/java/org/apache/shardingsphere/mode/metadata/refresher/ShardingSphereStatisticsRefreshEngine.java

@@ -20,6 +20,7 @@
 import lombok.extern.slf4j.Slf4j;
 import org.apache.shardingsphere.infra.config.props.temporary.TemporaryConfigurationPropertyKey;
 import org.apache.shardingsphere.infra.executor.kernel.thread.ExecutorThreadFactoryBuilder;
+import org.apache.shardingsphere.infra.instance.metadata.InstanceType;
 import org.apache.shardingsphere.infra.lock.LockContext;
 import org.apache.shardingsphere.infra.metadata.ShardingSphereMetaData;
 import org.apache.shardingsphere.infra.metadata.database.ShardingSphereDatabase;
@@ -68,7 +69,9 @@ public ShardingSphereStatisticsRefreshEngine(final ContextManager contextManager
      * Async refresh.
      */
     public void asyncRefresh() {
-        EXECUTOR_SERVICE.execute(this::refresh);
+        if (InstanceType.PROXY == contextManager.getComputeNodeInstanceContext().getInstance().getMetaData().getType()) {
+            EXECUTOR_SERVICE.execute(this::refresh);
+        }
     }
 
     /**