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社区首页 >专栏 >我也能写数据库 —— UDF

我也能写数据库 —— UDF

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麒思妙想
发布于 2020-07-10 13:19:47
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发布于 2020-07-10 13:19:47
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文章被收录于专栏：麒思妙想

直播改BUG

修复内联查询

在上期文章撰写的时候，我还认为只完成了单表查询，但经过几天的研究发现，上次那寥寥几十行代码，其实已经可以完成了表联接，过滤等功能了，只是由于当时粗心写错了一些东西，造成过滤失效了，下面我来剖析一下问题。

首先在Storage.java这个文件里

代码语言：javascript
复制
public class Storage {
   public static final String SCHEMA_NAME = "bookshop";
   public static final String TABLE_AUTHOR = "AUTHOR";
   public static final String TABLE_BOOK = "BOOK";//    public static List<DummyTable> tables = new ArrayList<>();
   public static Hashtable<String,DummyTable> _bag = new Hashtable<>();
   static{
       DummyTable author = new DummyTable(TABLE_AUTHOR);
       DummyColumn id = new DummyColumn("ID","String");
       DummyColumn name = new DummyColumn("NAME","String");
       DummyColumn age = new DummyColumn("AGE","String");
       DummyColumn aid = new DummyColumn("AID","String");
       DummyColumn type = new DummyColumn("TYPE","String");
       author.addColumn(id).addColumn(name).addColumn(age);
       author.addRow("1","jacky","33");
       author.addRow("2","wang","23");
       author.addRow("3","dd","32");
       author.addRow("4","ma","42");
//        tables.add(author);
       _bag.put(TABLE_AUTHOR,author);       DummyTable book = new DummyTable(TABLE_BOOK);
       book.addColumn(id).addColumn(name).addColumn(aid).addColumn(type);
       book.addRow("1","1","数据山","java");
       book.addRow("2","2","大关","sql");
       book.addRow("3","1","lili","sql");
       book.addRow("4","3","ten","c#");
//        tables.add(book);
       _bag.put(TABLE_BOOK,book);
   }
   ......
}

只截取了部分片段， 在book.addColumn(id).addColumn(name).addColumn(aid).addColumn(type);这里，我把name列和aid列写颠倒了。更正过来，就可以进行正确的连接查询了。

过滤条件

在可以进行内联查询以后，我一直在对不能做过滤这点存在质疑，从关系代数的角度分析，应该是先做笛卡尔积，然后再过滤数据，那么就应该可以对数据进行过滤了，那么问题出在哪呢？

于是抱着试试看的心里，构建了一条查询select * from "BOOK" as b where b.name = 数据山，看看效果，果不其然，喜闻乐见...

代码语言：javascript
复制
java.sql.SQLException: Error while executing SQL "select * from "BOOK" as b where b.name = 数据山": From line 1, column 42 to line 1, column 44: Column '数据山' not found in any table
at org.apache.calcite.avatica.Helper.createException(Helper.java:56)
at org.apache.calcite.avatica.Helper.createException(Helper.java:41)
at org.apache.calcite.avatica.AvaticaStatement.executeInternal(AvaticaStatement.java:163)
at org.apache.calcite.avatica.AvaticaStatement.executeQuery(AvaticaStatement.java:227)
at com.dafei1288.calcite.TestJDBC.main(TestJDBC.java:81)
Caused by: org.apache.calcite.runtime.CalciteContextException: From line 1, column 42 to line 1, column 44: Column '数据山' not found in any table
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:422)
at org.apache.calcite.runtime.Resources$ExInstWithCause.ex(Resources.java:463)
at org.apache.calcite.sql.SqlUtil.newContextException(SqlUtil.java:783)
at org.apache.calcite.sql.SqlUtil.newContextException(SqlUtil.java:768)
at org.apache.calcite.sql.validate.SqlValidatorImpl.newValidationError(SqlValidatorImpl.java:4759)
at org.apache.calcite.sql.validate.DelegatingScope.fullyQualify(DelegatingScope.java:259)
at org.apache.calcite.sql.validate.SqlValidatorImpl$Expander.visit(SqlValidatorImpl.java:5619)
at org.apache.calcite.sql.validate.SqlValidatorImpl$Expander.visit(SqlValidatorImpl.java:5601)
at org.apache.calcite.sql.SqlIdentifier.accept(SqlIdentifier.java:334)
at org.apache.calcite.sql.util.SqlShuttle$CallCopyingArgHandler.visitChild(SqlShuttle.java:134)
at org.apache.calcite.sql.util.SqlShuttle$CallCopyingArgHandler.visitChild(SqlShuttle.java:101)
at org.apache.calcite.sql.SqlOperator.acceptCall(SqlOperator.java:859)
at org.apache.calcite.sql.validate.SqlValidatorImpl$Expander.visitScoped(SqlValidatorImpl.java:5654)
at org.apache.calcite.sql.validate.SqlScopedShuttle.visit(SqlScopedShuttle.java:50)
at org.apache.calcite.sql.validate.SqlScopedShuttle.visit(SqlScopedShuttle.java:33)
at org.apache.calcite.sql.SqlCall.accept(SqlCall.java:138)
at org.apache.calcite.sql.validate.SqlValidatorImpl.expand(SqlValidatorImpl.java:5208)
at org.apache.calcite.sql.validate.SqlValidatorImpl.validateWhereClause(SqlValidatorImpl.java:3948)
at org.apache.calcite.sql.validate.SqlValidatorImpl.validateSelect(SqlValidatorImpl.java:3276)
at org.apache.calcite.sql.validate.SelectNamespace.validateImpl(SelectNamespace.java:60)
at org.apache.calcite.sql.validate.AbstractNamespace.validate(AbstractNamespace.java:84)
at org.apache.calcite.sql.validate.SqlValidatorImpl.validateNamespace(SqlValidatorImpl.java:967)
at org.apache.calcite.sql.validate.SqlValidatorImpl.validateQuery(SqlValidatorImpl.java:943)
at org.apache.calcite.sql.SqlSelect.validate(SqlSelect.java:225)
at org.apache.calcite.sql.validate.SqlValidatorImpl.validateScopedExpression(SqlValidatorImpl.java:918)
at org.apache.calcite.sql.validate.SqlValidatorImpl.validate(SqlValidatorImpl.java:628)
at org.apache.calcite.sql2rel.SqlToRelConverter.convertQuery(SqlToRelConverter.java:552)
at org.apache.calcite.prepare.Prepare.prepareSql(Prepare.java:264)
at org.apache.calcite.prepare.Prepare.prepareSql(Prepare.java:230)
at org.apache.calcite.prepare.CalcitePrepareImpl.prepare2_(CalcitePrepareImpl.java:772)
at org.apache.calcite.prepare.CalcitePrepareImpl.prepare_(CalcitePrepareImpl.java:636)
at org.apache.calcite.prepare.CalcitePrepareImpl.prepareSql(CalcitePrepareImpl.java:606)
at org.apache.calcite.jdbc.CalciteConnectionImpl.parseQuery(CalciteConnectionImpl.java:229)
at org.apache.calcite.jdbc.CalciteMetaImpl.prepareAndExecute(CalciteMetaImpl.java:550)
at org.apache.calcite.avatica.AvaticaConnection.prepareAndExecuteInternal(AvaticaConnection.java:675)
at org.apache.calcite.avatica.AvaticaStatement.executeInternal(AvaticaStatement.java:156)
... 2 more
Caused by: org.apache.calcite.sql.validate.SqlValidatorException: Column '数据山' not found in any table
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:422)
at org.apache.calcite.runtime.Resources$ExInstWithCause.ex(Resources.java:463)
at org.apache.calcite.runtime.Resources$ExInst.ex(Resources.java:572)
... 36 more

看到报错一脸懵逼，From line 1, column 42 to line 1, column 44: Column '数据山' not found in any table这是把过滤条件当列处理了？在百思不得其解的时候，突然想起了mysql的引号问题，于是把sql修正为select * from "BOOK" as b where b.name = '数据山'，于是喜闻乐见变了一下

代码语言：javascript
复制
java.sql.SQLException: Error while executing SQL "select * from "BOOK" as b where b.name = '数据山'": while converting `B`.`NAME` = '数据山'
at org.apache.calcite.avatica.Helper.createException(Helper.java:56)
at org.apache.calcite.avatica.Helper.createException(Helper.java:41)
at org.apache.calcite.avatica.AvaticaStatement.executeInternal(AvaticaStatement.java:163)
at org.apache.calcite.avatica.AvaticaStatement.executeQuery(AvaticaStatement.java:227)
at com.dafei1288.calcite.TestJDBC.main(TestJDBC.java:81)
Caused by: java.lang.RuntimeException: while converting `B`.`NAME` = '数据山'
at org.apache.calcite.sql2rel.ReflectiveConvertletTable.lambda$registerNodeTypeMethod$0(ReflectiveConvertletTable.java:86)
at org.apache.calcite.sql2rel.SqlNodeToRexConverterImpl.convertCall(SqlNodeToRexConverterImpl.java:63)
at org.apache.calcite.sql2rel.SqlToRelConverter$Blackboard.visit(SqlToRelConverter.java:4670)
at org.apache.calcite.sql2rel.SqlToRelConverter$Blackboard.visit(SqlToRelConverter.java:3977)
at org.apache.calcite.sql.SqlCall.accept(SqlCall.java:138)
at org.apache.calcite.sql2rel.SqlToRelConverter$Blackboard.convertExpression(SqlToRelConverter.java:4541)
at org.apache.calcite.sql2rel.SqlToRelConverter.convertWhere(SqlToRelConverter.java:965)
at org.apache.calcite.sql2rel.SqlToRelConverter.convertSelectImpl(SqlToRelConverter.java:643)
at org.apache.calcite.sql2rel.SqlToRelConverter.convertSelect(SqlToRelConverter.java:621)
at org.apache.calcite.sql2rel.SqlToRelConverter.convertQueryRecursive(SqlToRelConverter.java:3051)
at org.apache.calcite.sql2rel.SqlToRelConverter.convertQuery(SqlToRelConverter.java:557)
at org.apache.calcite.prepare.Prepare.prepareSql(Prepare.java:264)
at org.apache.calcite.prepare.Prepare.prepareSql(Prepare.java:230)
at org.apache.calcite.prepare.CalcitePrepareImpl.prepare2_(CalcitePrepareImpl.java:772)
at org.apache.calcite.prepare.CalcitePrepareImpl.prepare_(CalcitePrepareImpl.java:636)
at org.apache.calcite.prepare.CalcitePrepareImpl.prepareSql(CalcitePrepareImpl.java:606)
at org.apache.calcite.jdbc.CalciteConnectionImpl.parseQuery(CalciteConnectionImpl.java:229)
at org.apache.calcite.jdbc.CalciteMetaImpl.prepareAndExecute(CalciteMetaImpl.java:550)
at org.apache.calcite.avatica.AvaticaConnection.prepareAndExecuteInternal(AvaticaConnection.java:675)
at org.apache.calcite.avatica.AvaticaStatement.executeInternal(AvaticaStatement.java:156)
... 2 more
Caused by: java.lang.reflect.InvocationTargetException
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:497)
at org.apache.calcite.sql2rel.ReflectiveConvertletTable.lambda$registerNodeTypeMethod$0(ReflectiveConvertletTable.java:83)
... 21 more
Caused by: org.apache.calcite.runtime.CalciteException: Failed to encode '数据山' in character set 'ISO-8859-1'
at sun.reflect.NativeConstructorAccessorImpl.newInstance0(Native Method)
at sun.reflect.NativeConstructorAccessorImpl.newInstance(NativeConstructorAccessorImpl.java:62)
at sun.reflect.DelegatingConstructorAccessorImpl.newInstance(DelegatingConstructorAccessorImpl.java:45)
at java.lang.reflect.Constructor.newInstance(Constructor.java:422)
at org.apache.calcite.runtime.Resources$ExInstWithCause.ex(Resources.java:463)
at org.apache.calcite.runtime.Resources$ExInst.ex(Resources.java:572)
at org.apache.calcite.util.NlsString.<init>(NlsString.java:81)
at org.apache.calcite.rex.RexBuilder.makeLiteral(RexBuilder.java:878)
at org.apache.calcite.rex.RexBuilder.makeCharLiteral(RexBuilder.java:1093)
at org.apache.calcite.sql2rel.SqlNodeToRexConverterImpl.convertLiteral(SqlNodeToRexConverterImpl.java:118)
at org.apache.calcite.sql2rel.SqlToRelConverter$Blackboard.visit(SqlToRelConverter.java:4659)
at org.apache.calcite.sql2rel.SqlToRelConverter$Blackboard.visit(SqlToRelConverter.java:3977)
at org.apache.calcite.sql.SqlLiteral.accept(SqlLiteral.java:532)
at org.apache.calcite.sql2rel.SqlToRelConverter$Blackboard.convertExpression(SqlToRelConverter.java:4541)
at org.apache.calcite.sql2rel.StandardConvertletTable.convertExpressionList(StandardConvertletTable.java:767)
at org.apache.calcite.sql2rel.StandardConvertletTable.convertCall(StandardConvertletTable.java:743)
at org.apache.calcite.sql2rel.StandardConvertletTable.convertCall(StandardConvertletTable.java:727)
... 26 more

对于开发者来说，有变化总是好事，说明可能找到问题点了，再仔细看看日志，果然，编码问题，搞起。于是在各种检索下，得到了答案

代码语言：javascript
复制
System.setProperty("saffron.default.charset", ConversionUtil.NATIVE_UTF16_CHARSET_NAME);
System.setProperty("saffron.default.nationalcharset",ConversionUtil.NATIVE_UTF16_CHARSET_NAME);
System.setProperty("saffron.default.collation.name",ConversionUtil.NATIVE_UTF16_CHARSET_NAME + "$en_US");

在获取连接之前，将入上述环境变量，就好了,代码片段如下：

代码语言：javascript
复制
    public static void main(String[] args) {
       try {
           Class.forName("org.apache.calcite.jdbc.Driver");
       } catch (ClassNotFoundException e1) {
           e1.printStackTrace();
       }
       System.setProperty("saffron.default.charset", ConversionUtil.NATIVE_UTF16_CHARSET_NAME);
       System.setProperty("saffron.default.nationalcharset",ConversionUtil.NATIVE_UTF16_CHARSET_NAME);
       System.setProperty("saffron.default.collation.name",ConversionUtil.NATIVE_UTF16_CHARSET_NAME + "$en_US");       Properties info = new Properties();
       String jsonmodle = "E:\\working\\others\\写作\\calcitetutorial\\src\\main\\resources\\bookshop.json";
       
       Connection connection =
                   DriverManager.getConnection("jdbc:calcite:model="+jsonmodle, info);
       CalciteConnection calciteConn = connection.unwrap(CalciteConnection.class);
       ......
   }

数据类型处理

在写过滤的时候，其实就发现了，没有正确的数据类型，是走不远的，所以有必要把数据类型对应好，既然是模拟数据库，那么数据基本类型，还是使用SQL习惯的类型，而这里对java还是需要有一个映射关系。

代码语言：javascript
复制
package com.dafei1288.calcite.storage;import com.google.common.collect.HashBasedTable;
import com.google.common.collect.Table;
import org.apache.calcite.sql.type.SqlTypeName;import java.math.BigDecimal;
import java.sql.Date;
import java.util.Set;/**
* 这里使用了GUAVA的table 作为存SQL和JAVA数据类型的数据结构
* 这并不是一个好的设计，而是为了让大家更容易理解而做的设计
*/
public class DataTypeMapping {   public static Table<String, SqlTypeName,Class> TYPEMAPPING= HashBasedTable.create();
   public static final String CHAR = "char";
   public static final String VARCHAR = "varchar";
   public static final String BOOLEAN = "boolean";
   public static final String DATE = "date";
   public static final String INTEGER = "integer";
   public static final String TINYINT = "tinyint";
   public static final String SMALLINT = "smallint";
   public static final String BIGINT = "bigint";
   public static final String DECIMAL = "decimal";
   public static final String NUMERIC = "numeric";
   public static final String FLOAT = "float";
   public static final String REAL = "real";
   public static final String DOUBLE = "double";
   public static final String TIME = "time";
   public static final String TIMESTAMP = "timestamp";
   public static final String ANY = "any";
   static{
       TYPEMAPPING.put(DataTypeMapping.CHAR,SqlTypeName.CHAR,Character.class);
       TYPEMAPPING.put(DataTypeMapping.VARCHAR,SqlTypeName.VARCHAR,String.class);
       TYPEMAPPING.put(DataTypeMapping.BOOLEAN,SqlTypeName.BOOLEAN,Boolean.class);
       TYPEMAPPING.put(DataTypeMapping.DATE,SqlTypeName.DATE,Date.class);
       TYPEMAPPING.put(DataTypeMapping.INTEGER,SqlTypeName.INTEGER,Integer.class);
       TYPEMAPPING.put(DataTypeMapping.TINYINT, SqlTypeName.TINYINT,Integer.class);
       TYPEMAPPING.put(DataTypeMapping.SMALLINT, SqlTypeName.SMALLINT,Integer.class);
       TYPEMAPPING.put(DataTypeMapping.BIGINT, SqlTypeName.BIGINT,Long.class);
       TYPEMAPPING.put(DataTypeMapping.DECIMAL, SqlTypeName.DECIMAL, BigDecimal.class);
       TYPEMAPPING.put(DataTypeMapping.NUMERIC, SqlTypeName.DECIMAL,Long.class);
       TYPEMAPPING.put(DataTypeMapping.FLOAT, SqlTypeName.FLOAT,Float.class);
       TYPEMAPPING.put(DataTypeMapping.REAL, SqlTypeName.REAL,Double.class);
       TYPEMAPPING.put(DataTypeMapping.DOUBLE, SqlTypeName.DOUBLE,Double.class);
       TYPEMAPPING.put(DataTypeMapping.TIME, SqlTypeName.TIME, Date.class);
       TYPEMAPPING.put(DataTypeMapping.TIMESTAMP, SqlTypeName.TIMESTAMP,Long.class);
       TYPEMAPPING.put(DataTypeMapping.ANY, SqlTypeName.ANY,String.class);
   }
   /**
    * 根据名字获取，对应的java类型
    * */
   public static Class getJavaClassByName(String name){
       Set<Table.Cell<String, SqlTypeName,Class>> table = TYPEMAPPING.cellSet();
       for(Table.Cell<String, SqlTypeName,Class> it:table){
           if(it.getRowKey().equals(name)){
               return it.getValue();
           }
       }
       return null;
   }
   public static SqlTypeName getSqlTypeByName(String name){
       for(Table.Cell<String, SqlTypeName,Class> it:TYPEMAPPING.cellSet()){
           if(it.getRowKey().equals(name)){
               return it.getColumnKey();
           }
       }
       return null;
   }
}

栗子中，我使用了guava的table结构，主要还是为了大家方便只管理解，Table<String, SqlTypeName,Class>,第一个泛型代表内部定义的数据类型字符串，第二个是SQL数据类型，第三个参数是对应的JAVA类型。由于guava的table是xy-->z模式，但实际上我们需要的是一个x->yz模式，所以在下面添加了两个辅助方法：public static Class getJavaClassByName(String name)通过拿到的数据类型的字符串，获得java的类型，public static SqlTypeName getSqlTypeByName(String name)这个方法则是拿到SQL的数据类型。

笔者一直对充血模型钟爱有加，所以在Storage里为DummyColumn添加了两个方法

代码语言：javascript
复制
public static class DummyColumn{
       private String name;
       private String type;       public DummyColumn(String name, String type) {
           this.name = name;
           this.type = type;
       }       public String getName() {
           return name;
       }       public String getType() {
           return type;
       }       public void setName(String name) {
           this.name = name;
       }       public void setType(String type) {
           this.type = type;
       }       //充血模型
       //获取JAVA类型
       public Class getJavaClass(){
           return DataTypeMapping.getJavaClassByName(this.type);
       }       public SqlTypeName getSqlTypeName(){
           return DataTypeMapping.getSqlTypeByName(this.type);
       }
   }

而在数据初始化的时候，我们可以使用正确的数据类型了

代码语言：javascript
复制
        DummyColumn id = new DummyColumn("ID","integer");
       DummyColumn name = new DummyColumn("NAME","varchar");
       DummyColumn age = new DummyColumn("AGE","integer");
       DummyColumn aid = new DummyColumn("AID","integer");
       DummyColumn type = new DummyColumn("TYPE","varchar");

这样数据类型的准备工作就做好了，后面我们需要将数据类型正确的注册表里，所以在InMemoryTable里我们原来写死的String.class类型，需要根据实际数据进行设置了

代码语言：javascript
复制
 @Override
   public RelDataType getRowType(RelDataTypeFactory typeFactory) {
//        System.out.println("RelDataType !!!!!!");
       if(dataType == null) {
           RelDataTypeFactory.FieldInfoBuilder fieldInfo = typeFactory.builder();
           for (Storage.DummyColumn column : this._table.getColumns()) {
               RelDataType sqlType = typeFactory.createJavaType(column.getJavaClass()); //这里使用了新增的方法，原来是String.class
               sqlType = SqlTypeUtil.addCharsetAndCollation(sqlType, typeFactory);
               fieldInfo.add(column.getName(), sqlType);
           }
           this.dataType = typeFactory.createStructType(fieldInfo);
       }
       return this.dataType;
   }

到这里我们就搞定了数据类型。

UDF

有了基础数据类型，对于我们后面做函数处理就方便多了，现在我们以2个简单的UDF为例，让我们继续领略calcite的魅力，

首先我们定义两个类，一个数学类，提供一个乘方的方法

代码语言：javascript
复制
package com.dafei1288.calcite.function;public class MathFunction {
   public int square(int i){
       return i*i;
   }
}

另一个字符处理类，提供一个字符串连接方法，提供一个将参数转换成字符串的方法

代码语言：javascript
复制
package com.dafei1288.calcite.function;public class StringFunction {
   public String concat(Object o1,Object o2){
       return "["+o1.toString()+" , "+o2.toString()+"] => "+this.toString();
   }
   public String parseString(Object o){
       return o.toString();
   }
}

接下来，在InMemorySchemaFactory里，将函数注册到数据库上，

代码语言：javascript
复制
package com.dafei1288.calcite;import com.dafei1288.calcite.function.MathFunction;
import com.dafei1288.calcite.function.StringFunction;
import org.apache.calcite.schema.Schema;
import org.apache.calcite.schema.SchemaFactory;
import org.apache.calcite.schema.SchemaPlus;
import org.apache.calcite.schema.impl.ScalarFunctionImpl;import java.util.Map;public class InMemorySchemaFactory implements SchemaFactory {
   @Override
   public Schema create(SchemaPlus parentSchema, String name, Map<String, Object> operand) {       System.out.println("schema name ==>  "+ name);
       System.out.println("operand ==> "+operand);       parentSchema.add("SQUARE_FUNC",ScalarFunctionImpl.create(MathFunction.class,"square"));
       parentSchema.add("TOSTRING_FUNC",ScalarFunctionImpl.create(StringFunction.class,"parseString"));
       parentSchema.add("CONCAT_FUNC",ScalarFunctionImpl.create(StringFunction.class,"concat"));       return new InMemorySchema(name,operand);
   }
}

SchemaPlus parentSchema提供了一个void add(String name, Function function)方法，name为函数名，这里calcite提供了一个工具类ScalarFunction,它可以通过create方法，可以将你写好的函数类和其对应的方法反射出来。

接下来我们做一个测试：

代码语言：javascript
复制
result = st.executeQuery("select SQUARE_FUNC(b.id),CONCAT_FUNC(b.id,b.name) from \"BOOK\" as b");
while(result.next()) {
   System.out.println(result.getString(1) + "\t" +result.getString(2) + "\t" );
}

结果

代码语言：javascript
复制
1	[1 , 数据山] => com.dafei1288.calcite.function.StringFunction@22bb5646
4	[2 , 大关] => com.dafei1288.calcite.function.StringFunction@1be59f28
9	[3 , lili] => com.dafei1288.calcite.function.StringFunction@2ce45a7b
16	[4 , ten] => com.dafei1288.calcite.function.StringFunction@153d4abb

技术总结

这期新内容代码有点少，但是在实验成功以后，就克不住自己的兴奋了，一蹴而就写了这篇文章。

后续：

  1. 希望能对聚合函数做一些尝试。
  2. 函数的下推，这只是一个想法，目前实现的还是相当于UDF，那么实际上数据库层应该提供了很多函数的，那么在这里，是否可以透过calcite将函数交给Storage处理...
  3. streaming sql

代码已更新：https://github.com/dafei1288/CalciteHelloworld.git

文档的翻译工作感觉暂时鸽了：）

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原始发表：2018-12-19，如有侵权请联系 cloudcommunity@tencent.com 删除
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目录
  • 直播改BUG
    • 修复内联查询
      • 过滤条件
      • 数据类型处理
      • UDF
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