语法解析器续:case..when..语法解析计算

时间:2023-03-09 05:17:43
语法解析器续:case..when..语法解析计算

  之前写过一篇博客,是关于如何解析类似sql之类的解析器实现参考:https://www.cnblogs.com/yougewe/p/13774289.html

  之前的解析器,更多的是是做语言的翻译转换工作,并不涉及具体的数据运算。而且抛弃了许多上下文关联语法处理,所以相对还是简单的。

  那么,如果我们想做一下数据运算呢?比如我给你一些值,然后给你一个表达式,你可以给出其运算结果吗?

1. 表达式运算难度如何?

  比如,已知表达式为, field1 > 0 and field2 > 0, 然后已知道值 field1 = 1, field2 = 2; 那么,此运算结果必当为true。这很理所当然!

  但以上,仅为人工处理,自己用大脑做了下运算,得到结果。如果转换为代码,又当如何?

  我想,我们至少要做这么几件事:

    1. 解析出所有字段有field1, field2;
    2. 解析出比较运算符 >;
    3. 解析出右边具体的比较值;
    4. 解析出连接运算符and;
    5. 做所有的比较运算;
    6. 关联优先级得到最终结果;

  怎么样?现在还觉得很简单吗?如果是,请收下我的膝盖!

  但是,如果真要做这种泛化的场景,那就相当相当复杂了,要知道类似于HIVE之类的重量级产品,语法解析都是其中重要的组成部分。实际上,这可能涉及到相当多的语言规范需要做了。所以,必然超出我们的简化理解范围。

  所以,我这里仅挑一个简单场景做解析:即如题所说,case..when..的解析。

  所以,我们可以范围缩减为,给定表达式:case when field1 > 0 then 'f1' else 'fn' end; 的判断解析。比如给定值 field1=1, 则应得到结果 f1, 如果给定值 field1=0, 则应得到结果 fn.

  在划定范围之后,好像更有了目标感了。但是问题真的简单了吗?实际上,还是有相当多的分支需要处理的,因为case..when..中可以嵌套其他语法。所以,我们只能尽力而为了。

2. case..when..表达式运算的实现

  命题确立之后,我们可以开始着手如何实现了。如上描述,我们有两个已知条件:表达式和基础值。

  基于上一篇文章的解析,我们基本可以快速得到所有组成case when 的元素token信息了。这就为我们省去了不少事。这里,我着重给一个如何获取整个case..when..词句的实现,使其可形成一个独立的词组。

    // 将case..when.. 归结为sql类关键词的实现中
public SqlKeywordAstHandler(TokenDescriptor masterToken,
Iterator<TokenDescriptor> candidates,
TokenTypeEnum tokenType) {
super(masterToken, candidates, tokenType);
String word = masterToken.getRawWord().toLowerCase();
if("case".equals(word)) {
completeCaseWhenTokens(candidates);
}
} /**
* 实例case...when... 词汇列表
*
* @param candidates 待用词汇
*/
private void completeCaseWhenTokens(Iterator<TokenDescriptor> candidates) {
boolean syntaxClosed = false;
while (candidates.hasNext()) {
TokenDescriptor token = candidates.next();
addExtendToken(token);
if("end".equalsIgnoreCase(token.getRawWord())) {
syntaxClosed = true;
break;
}
}
if(!syntaxClosed) {
throw new SyntaxException("语法错误:case..when..未半闭合");
}
}

  以上,就是获取case..when..词组的方法了,主要就是从case开始,到end结束,中间的所有词根,都被划作其范围。当然,还有一个重要的点,是将数据字段找出来,放到可取到的地方。

  有了一个个独立的元素,我们就可以进行语义分析了。该分析可以放在该解析器中,但也许并不会太通用,所以,此处我将其抽象为一个单独的值运算类。在需要的地方,再实例化该运算类,即可。核心问题如上一节中描述,具体实现代码如下:

import com.my.mvc.app.common.exception.SyntaxException;
import com.my.mvc.app.common.helper.parser.SyntaxStatement;
import com.my.mvc.app.common.helper.parser.TokenDescriptor;
import com.my.mvc.app.common.helper.parser.TokenTypeEnum;
import lombok.extern.slf4j.Slf4j;
import org.apache.commons.lang3.StringUtils; import java.math.BigDecimal;
import java.util.*;
import java.util.stream.Collectors; /**
* 功能描述: case..when.. 真实数据运算帮助类
*
*/
@Slf4j
public class CaseWhenElDataCalcHelper { /**
* case when 完整语法
*/
private SyntaxStatement caseWhenStmt; public CaseWhenElDataCalcHelper(SyntaxStatement caseWhenStmt) {
this.caseWhenStmt = caseWhenStmt;
} /**
* 计算case..when的结果
*
* @param suppliers 原始所有值
* @return 最终计算出的值
*/
public String calcCaseWhenData(Map<String, String> suppliers) {
List<TokenDescriptor> allTokens = caseWhenStmt.getAllTokens();
TokenDescriptor masterToken = allTokens.get(0);
if(!"case".equalsIgnoreCase(masterToken.getRawWord())) {
throw new SyntaxException("不是case..when..表达式");
}
int tokenLen = allTokens.size();
if(tokenLen < 3) {
throw new SyntaxException("case..when..表达式语法错误");
}
TokenDescriptor closureToken = allTokens.get(tokenLen - 1);
if(!"end".equalsIgnoreCase(closureToken.getRawWord())) {
throw new SyntaxException("case..when..表达式未闭合");
}
// 暂只支持 case when xxx then xxx... end 语法
// 不支持 case field_name when 1 then '1'... end, 即单字段判定不支持
List<TokenDescriptor> whenExpressionCandidates;
for (int i = 1; i < tokenLen - 1; i++) {
whenExpressionCandidates = new ArrayList<>();
TokenDescriptor currentToken = allTokens.get(i);
if("when".equalsIgnoreCase(currentToken.getRawWord())) {
// 需走各分支逻辑
while (i + 1 < tokenLen) {
TokenDescriptor nextToken = allTokens.get(i + 1);
if("then".equalsIgnoreCase(nextToken.getRawWord())) {
break;
}
whenExpressionCandidates.add(nextToken);
++i;
}
if(judgeWhenExpression(whenExpressionCandidates, suppliers)) {
List<TokenDescriptor> resultCandidates
= scrapeCaseWhenResultCandidates(allTokens, i + 1);
return calcExpressionData(resultCandidates, suppliers);
}
// 直接进入下一轮迭代,then后面为空迭代
}
if("else".equalsIgnoreCase(currentToken.getRawWord())) {
List<TokenDescriptor> resultCandidates
= scrapeCaseWhenResultCandidates(allTokens, i);
return calcExpressionData(resultCandidates, suppliers);
}
}
return null;
} /**
* 捞出所有的结果运算token列表
*
* @param allTokens 全局token表
* @param start 偏移量
* @return 获取到的所有结果运算token
*/
private List<TokenDescriptor> scrapeCaseWhenResultCandidates(List<TokenDescriptor> allTokens,
int start) {
List<TokenDescriptor> resultCandidates = new ArrayList<>();
while (start + 1 < allTokens.size()) {
TokenDescriptor nextToken = allTokens.get(start + 1);
String word = nextToken.getRawWord();
if("when".equalsIgnoreCase(word)
|| "else".equalsIgnoreCase(word)
|| "end".equalsIgnoreCase(word)) {
break;
}
resultCandidates.add(nextToken);
++start;
}
return resultCandidates;
} /**
* 判断when条件是否成立
*
* @param operatorCandidates 可供运算的表达式token列表
* @param suppliers 原始字段取值来源
* @return true:符合该判定,false:判定失败
*/
private boolean judgeWhenExpression(List<TokenDescriptor> operatorCandidates,
Map<String, String> suppliers) {
List<AndOrOperatorSupervisor> supervisors
= partitionByPriority(operatorCandidates);
boolean prevJudgeSuccess = false;
for (AndOrOperatorSupervisor calc1 : supervisors) {
Map<String, List<TokenDescriptor>> unitGroup = calc1.getUnitGroupTokens();
String leftValue = calcExpressionData(unitGroup.get("LEFT"), suppliers);
String op = unitGroup.get("OP").get(0).getRawWord();
TokenTypeEnum resultType = getPriorDataTypeByTokenList(unitGroup.get("RIGHT"));
boolean myJudgeSuccess;
if("in".equals(op)) {
myJudgeSuccess = checkExistsIn(leftValue, unitGroup.get("RIGHT"), resultType);
}
else if("notin".equals(op)) {
myJudgeSuccess = !checkExistsIn(leftValue, unitGroup.get("RIGHT"), resultType);
}
else {
String rightValue = calcExpressionData(unitGroup.get("RIGHT"), suppliers);
myJudgeSuccess = checkCompareTrue(leftValue, op,
rightValue, resultType);
}
TokenDescriptor prevType = calc1.getPrevType();
TokenDescriptor nextType = calc1.getNextType();
// 单条件判定
if(prevType == null && nextType == null) {
return myJudgeSuccess;
}
if(nextType == null) {
return myJudgeSuccess;
}
prevJudgeSuccess = myJudgeSuccess;
if("and".equalsIgnoreCase(nextType.getRawWord())) {
if(!myJudgeSuccess) {
return false;
}
continue;
}
if("or".equalsIgnoreCase(nextType.getRawWord())) {
if(myJudgeSuccess) {
return true;
}
continue;
}
log.warn("解析到未知的next连接判定符:{}", nextType);
throw new SyntaxException("语法解析错误");
}
log.warn("未判定出结果,使用默认返回,请检查");
return false;
} /**
* 根据值信息推断运算数据类型
*
* @param tokenList 结果列表(待运算)
* @return 计算的数据类型,数字或字符串
*/
private TokenTypeEnum getPriorDataTypeByTokenList(List<TokenDescriptor> tokenList) {
for (TokenDescriptor token : tokenList) {
if(token.getTokenType() == TokenTypeEnum.WORD_STRING) {
return TokenTypeEnum.WORD_STRING;
}
}
return TokenTypeEnum.WORD_NUMBER;
} /**
* 运算返回具体的 判定值
*
* @param resultCandidates 结果表达式token列表
* @param suppliers 原始字段取值来源
* @return true:符合该判定,false:判定失败
*/
private String calcExpressionData(List<TokenDescriptor> resultCandidates,
Map<String, String> suppliers) {
// 暂时假设结果中不再提供运算处理
TokenDescriptor first = resultCandidates.get(0);
if(first.getTokenType() == TokenTypeEnum.WORD_NORMAL) {
if("null".equalsIgnoreCase(first.getRawWord())) {
return null;
}
return suppliers.get(first.getRawWord());
}
return unwrapStringToken(first.getRawWord());
} /**
* 判断给定值是否在列表中
*
* @param aValue 要判定的值
* @param itemList 范围表
* @return true:成立, false:不在其中
*/
private boolean checkExistsIn(String aValue,
List<TokenDescriptor> itemList,
TokenTypeEnum valueType) {
if(aValue == null) {
return false;
}
BigDecimal aValueNumber = null;
for (TokenDescriptor tk1 : itemList) {
if(valueType == TokenTypeEnum.WORD_NUMBER) {
if(aValueNumber == null) {
aValueNumber = new BigDecimal(aValue);
}
if(aValueNumber.compareTo(
new BigDecimal(tk1.getRawWord())) == 0) {
return true;
}
continue;
}
if(aValue.equals(unwrapStringToken(tk1.getRawWord()))) {
return true;
}
}
return false;
} /**
* 将字符串两边的引号去除,保持字符串属性
*
* @param wrappedStr 含引号的字符串,如 'abc',"abc"
* @return abc 无引号包裹的字符串
*/
private String unwrapStringToken(String wrappedStr) {
if(wrappedStr == null || wrappedStr.length() == 0) {
return null;
}
char[] values = wrappedStr.toCharArray();
int i = 0;
while (i < values.length - 1
&& (values[i] == '"' || values[i] == '\'')) {
i++;
}
int j = values.length - 1;
while (j > 0
&& (values[j] == '"' || values[j] == '\'')) {
j--;
}
return new String(values, i, j - i + 1);
} /**
* 比较两个值ab是否基于op成立
*
* @param aValue 左值
* @param op 比较运算符
* @param bValue 右值
* @param valueType 值类型, 主要是区分数字与字符
* @return 是否等式成立, true:成立, false:不成立
*/
private boolean checkCompareTrue(String aValue,
String op,
String bValue,
TokenTypeEnum valueType) {
// 首先进行相生性判定
if("null".equals(bValue)) {
bValue = null;
}
switch(op) {
case "=":
if(bValue == null) {
return aValue == null;
}
return bValue.equals(aValue);
case "!=":
case "<>":
if(bValue == null) {
return aValue != null;
}
return !bValue.equals(aValue);
}
if(bValue == null) {
log.warn("非null值不能用比较符号运算");
throw new SyntaxException("语法错误");
}
// >=,<=,>,< 判定
int compareResult = compareTwoData(aValue, bValue, valueType);
switch(op) {
case ">":
return compareResult > 0;
case ">=":
return compareResult >= 0;
case "<=":
return compareResult <= 0;
case "<":
return compareResult < 0;
}
throw new SyntaxException("未知的运算符");
}
// 比较两个值大小ab
private int compareTwoData(String aValue,
String bValue,
TokenTypeEnum tokenType) {
bValue = unwrapStringToken(bValue);
if(bValue == null) {
// 按任意值大于null 规则处理
return aValue == null ? 0 : 1;
}
if(tokenType == TokenTypeEnum.WORD_NUMBER) {
return new BigDecimal(aValue).compareTo(
new BigDecimal(bValue));
}
return aValue.compareTo(unwrapStringToken(bValue));
} // 将token重新分组,以便可以做原子运算
private List<AndOrOperatorSupervisor> partitionByPriority(List<TokenDescriptor> tokens) {
// 1. 取左等式token列表
// 2. 取等式表达式
// 3. 取右等式token列表
// 4. 构建一个表达式,做最小分组
// 5. 检查是否有下一运算符,如有则必定为and|or|(
// 6. 保存上一连接判定符,新开一个分组
// 7. 重复步骤1-6,直到取完所有token // 前置运算符,决定是否要运算本节点,以及结果的合并方式
// 比如 and, 则当前点必须参与运算,如果前节点结果为false,则直接返回false
// 否则先计算本节点
TokenDescriptor preType = null;
// 当前节点计算完成后,判断下一运算是否有必要触发
// 为and时则当前为true时必须触发,为or时当前为false触发
TokenDescriptor nextType = null;
// key 为 left, op, right, 各value为细分tks
Map<String, List<TokenDescriptor>> unitGroup = new HashMap<>();
String currentReadPos = "LEFT";
List<TokenDescriptor> smallGroupTokenList = new ArrayList<>();
// 以上为描述单个运算的字符,使用一个list就可以描述无括号的表达式了
List<AndOrOperatorSupervisor> bracketGroup = new ArrayList<>();
AndOrOperatorSupervisor supervisor
= new AndOrOperatorSupervisor(null, unitGroup);
bracketGroup.add(supervisor);
for (int i = 0; i < tokens.size(); i++) {
TokenDescriptor token = tokens.get(i);
String word = token.getRawWord().toLowerCase();
TokenTypeEnum tokenType = token.getTokenType();
// 忽略分隔符,假设只有一级运算,忽略空格带来的复杂优先级问题
if(tokenType == TokenTypeEnum.CLAUSE_SEPARATOR) {
continue;
}
// 字段直接判定
if(tokenType == TokenTypeEnum.COMPARE_OPERATOR
&& !",".equals(word)) {
unitGroup.put("OP", Collections.singletonList(token));
currentReadPos = "RIGHT";
continue;
}
// is null, is not null 解析
if("is".equals(word)) {
while (i + 1 < tokens.size()) {
TokenDescriptor nextToken = tokens.get(i + 1);
if("null".equalsIgnoreCase(nextToken.getRawWord())) {
TokenDescriptor opToken = new TokenDescriptor("=",
TokenTypeEnum.COMPARE_OPERATOR);
unitGroup.put("OP", Collections.singletonList(opToken));
currentReadPos = "RIGHT";
List<TokenDescriptor> curTokenList = unitGroup.computeIfAbsent(
currentReadPos, r -> new ArrayList<>());
curTokenList.add(nextToken);
// 跳过1个token
i += 1;
break;
}
if("not".equalsIgnoreCase(nextToken.getRawWord())) {
if(i + 2 >= tokens.size()) {
throw new SyntaxException("语法错误3: is");
}
nextToken = tokens.get(i + 2);
if(!"null".equalsIgnoreCase(nextToken.getRawWord())) {
throw new SyntaxException("语法错误4: is");
}
TokenDescriptor opToken = new TokenDescriptor("!=",
TokenTypeEnum.COMPARE_OPERATOR);
unitGroup.put("OP", Collections.singletonList(opToken));
currentReadPos = "RIGHT";
List<TokenDescriptor> curTokenList = unitGroup.computeIfAbsent(
currentReadPos, r -> new ArrayList<>());
curTokenList.add(nextToken);
// 跳过2个token
i += 2;
break;
}
}
continue;
}
// in (x,x,xx) 语法解析
if("in".equals(word)) {
TokenDescriptor opToken = new TokenDescriptor("in",
TokenTypeEnum.COMPARE_OPERATOR);
unitGroup.put("OP", Collections.singletonList(opToken));
currentReadPos = "RIGHT";
List<TokenDescriptor> curTokenList = unitGroup.computeIfAbsent(
currentReadPos, r -> new ArrayList<>());
i = parseInItems(tokens, curTokenList, i);
continue;
}
// not in (x,xxx,xx) 语法解析
if("not".equals(word)) {
if(i + 1 > tokens.size()) {
throw new SyntaxException("语法错误:not");
}
TokenDescriptor nextToken = tokens.get(i + 1);
// 暂不支持 not exists 等语法
if(!"in".equalsIgnoreCase(nextToken.getRawWord())) {
throw new SyntaxException("不支持的语法:not");
}
TokenDescriptor opToken = new TokenDescriptor("notin",
TokenTypeEnum.COMPARE_OPERATOR);
unitGroup.put("OP", Collections.singletonList(opToken));
currentReadPos = "RIGHT";
List<TokenDescriptor> curTokenList = unitGroup.computeIfAbsent(
currentReadPos, r -> new ArrayList<>());
i = parseInItems(tokens, curTokenList, i + 1);
continue;
}
// 暂只解析一级,无括号情况
if("and".equals(word)
|| "or".equals(word)) {
supervisor.setNextType(token);
// 滚动到下一运算分支
unitGroup = new HashMap<>();
supervisor = new AndOrOperatorSupervisor(token, unitGroup);
bracketGroup.add(supervisor);
currentReadPos = "LEFT";
continue;
}
List<TokenDescriptor> curTokenList = unitGroup.computeIfAbsent(
currentReadPos, r -> new ArrayList<>());
curTokenList.add(token);
} return bracketGroup;
} /**
* 解析in中的所有元素到结果中
*
* @param tokens 所有token
* @param curTokenList 当前结果表
* @param start in 开始的地方
* @return in 语法结束位置
*/
private int parseInItems(List<TokenDescriptor> tokens,
List<TokenDescriptor> curTokenList,
int start) {
while (start + 1 < tokens.size()) {
TokenDescriptor nextToken = tokens.get(++start);
String nextWord = nextToken.getRawWord();
if("(".equals(nextWord)
|| ",".equals(nextWord)) {
// in 开始
continue;
}
if(")".equals(nextWord)) {
break;
}
curTokenList.add(nextToken);
}
return start;
} /**
* 最小运算单元描述符
*/
private class AndOrOperatorSupervisor {
// 前置运算符,决定是否要运算本节点,以及结果的合并方式
// 比如 and, 则当前点必须参与运算,如果前节点结果为false,则直接返回false
// 否则先计算本节点
TokenDescriptor prevType;
// 当前节点计算完成后,判断下一运算是否有必要触发
// 为and时则当前为true时必须触发,为or时当前为false触发
TokenDescriptor nextType;
// key 为 left, op, right, 各value为细分tks
Map<String, List<TokenDescriptor>> unitGroupTokens; public AndOrOperatorSupervisor(TokenDescriptor prevType,
Map<String, List<TokenDescriptor>> unitGroupTokens) {
this.prevType = prevType;
this.unitGroupTokens = unitGroupTokens;
} public void setNextType(TokenDescriptor nextType) {
this.nextType = nextType;
} public TokenDescriptor getPrevType() {
return prevType;
} public TokenDescriptor getNextType() {
return nextType;
} public Map<String, List<TokenDescriptor>> getUnitGroupTokens() {
return unitGroupTokens;
} @Override
public String toString() {
return StringUtils.join(
unitGroupTokens.get("LEFT").stream()
.map(TokenDescriptor::getRawWord)
.collect(Collectors.toList()), ' ')
+ unitGroupTokens.get("OP").get(0).getRawWord()
+
StringUtils.join(
unitGroupTokens.get("RIGHT").stream()
.map(TokenDescriptor::getRawWord)
.collect(Collectors.toList()), ' ') +
", prev=" + prevType
+ ", next=" + nextType
;
}
}
}

  每使用时,传入case..when..的语句构造出一个新的计算实例,然后调用 calcCaseWhenData(rawData), 带入已知参数信息,即可运算出最终的case..when..值。

  为使处理简单起见,这里并没有深入各种逻辑嵌套处理,直接忽略掉括号的处理了。另外,对于数值类的运算也暂时被忽略,如 field1 > 1+1 这种运算,并不会计算出2来。这些东西,需要的同学,完全可以稍加完善,即可支持处理这些逻辑。

  因 case when 的语法还是比较清晰的,所以我们只是做了顺序地读取,判定即得出结果。另外对于 case when 的单值判定并不支持,所以实现并不复杂。但这完全不影响我们理解整个语法处理的思想。相信需要的同学定能有所启发。

3. 表达式计算单元测试

  以上仅实现代码,需要附加上各种场景测试,才算可以work的东西。主要就是针对种 and/or, in, is null 等的处理。如下:

import com.my.mvc.app.common.helper.CaseWhenElDataCalcHelper;
import com.my.mvc.app.common.helper.SimpleSyntaxParser;
import com.my.mvc.app.common.helper.parser.ParsedClauseAst;
import lombok.extern.slf4j.Slf4j;
import org.junit.Assert;
import org.junit.Test; import java.util.HashMap;
import java.util.Map; @Slf4j
public class CaseWhenElDataCalcHelperTest {
@Test
public void testCaseWhenSimple1() {
String condition;
ParsedClauseAst parsedClause;
CaseWhenElDataCalcHelper helper;
Map<String, String> rawData;
condition = "case \n" +
"\twhen (kehu_phone is null or field1 != 'c') then m_phone \n" +
"\telse kehu_phone\n" +
"end";
parsedClause = SimpleSyntaxParser.parse(condition);
helper = new CaseWhenElDataCalcHelper(parsedClause.getAst().get(0));
rawData = new HashMap<>();
rawData.put("kehu_phone", "kehu_phone_v1");
rawData.put("field1", "field1_v");
rawData.put("m_phone", "m_phone_v");
Assert.assertEquals("case..when..中解析字段信息不正确",
3, parsedClause.getIdMapping().size());
Assert.assertEquals("case..when..解析结果错误",
rawData.get("m_phone"),
helper.calcCaseWhenData(rawData)); condition = "case \n" +
"\twhen (kehu_phone is null) then m_phone \n" +
"\telse kehu_phone\n" +
"end";
parsedClause = SimpleSyntaxParser.parse(condition);
helper = new CaseWhenElDataCalcHelper(parsedClause.getAst().get(0));
rawData = new HashMap<>();
rawData.put("kehu_phone", "kehu_phone_v1");
rawData.put("field1", "field1_v");
rawData.put("m_phone", "m_phone_v");
Assert.assertEquals("case..when..中解析字段信息不正确",
2, parsedClause.getIdMapping().size());
Assert.assertEquals("case..when..解析结果错误",
rawData.get("kehu_phone"),
helper.calcCaseWhenData(rawData)); rawData.remove("kehu_phone");
Assert.assertEquals("case..when..解析结果错误",
rawData.get("m_phone"),
helper.calcCaseWhenData(rawData)); condition = " case \n" +
" \twhen is_sx_emp='Y' then 'Y1' \n" +
" \twhen is_sx_new_custom!='Y' then 'Y2' \n" +
" \twhen is_sx_fort_promot_custom='Y' then 'Y3' \n" +
" \twhen promotion_role_chn in ('10','11') and first_tenthousand_dt is not null then 'Y4' \n" +
" \telse 'N' \n" +
" end";
parsedClause = SimpleSyntaxParser.parse(condition);
helper = new CaseWhenElDataCalcHelper(parsedClause.getAst().get(0));
rawData = new HashMap<>();
rawData.put("is_sx_emp", "N");
rawData.put("is_sx_new_custom", "Y");
rawData.put("is_sx_fortune_promot_custom", "N");
rawData.put("promotion_role_chn", "10");
rawData.put("first_tenthousand_dt", "10");
Assert.assertEquals("case..when..中解析字段信息不正确",
5, parsedClause.getIdMapping().size());
Assert.assertEquals("case..when..in解析结果错误",
"Y4",
helper.calcCaseWhenData(rawData)); rawData = new HashMap<>();
rawData.put("is_sx_emp", "N");
rawData.put("is_sx_new_custom", "Y");
rawData.put("is_sx_fortune_promot_custom", "N");
rawData.put("first_tenthousand_dt", "10");
rawData.put("promotion_role_chn", "9");
Assert.assertEquals("case..when..else解析结果错误",
"N",
helper.calcCaseWhenData(rawData)); rawData = new HashMap<>();
rawData.put("is_sx_new_custom", "Y");
rawData.put("is_sx_fortune_promot_custom", "N");
rawData.put("first_tenthousand_dt", "10");
rawData.put("promotion_role_chn", "9");
rawData.put("is_sx_emp", "Y");
Assert.assertEquals("case..when..=解析结果错误",
"Y1",
helper.calcCaseWhenData(rawData)); rawData = new HashMap<>();
rawData.put("is_sx_emp", "N");
rawData.put("is_sx_new_custom", "N");
rawData.put("is_sx_fortune_promot_custom", "N");
rawData.put("first_tenthousand_dt", "10");
rawData.put("promotion_role_chn", "9");
Assert.assertEquals("case..when..!=解析结果错误",
"Y2",
helper.calcCaseWhenData(rawData)); rawData = new HashMap<>();
rawData.put("is_sx_emp", "N");
rawData.put("is_sx_new_custom", "Y");
rawData.put("is_sx_fortune_promot_custom", "N");
// rawData.put("first_tenthousand_dt", "10");
rawData.put("promotion_role_chn", "9");
Assert.assertEquals("case..when..in+and+null解析结果错误",
"N",
helper.calcCaseWhenData(rawData)); condition = " case \n" +
" \twhen is_sx_emp='Y' then 'Y1' \n" +
" \twhen or_emp != null or or_emp2 > 3 then 'Y2_OR' \n" +
" \twhen and_emp != null and and_emp2 > 3 or or_tmp3 <= 10 then 'Y3_OR' \n" +
" \twhen promotion_role_chn not in ('10','11') and first_tenthousand_dt is not null then 'Y4' \n" +
" \twhen promotion_role_chn not in ('10') then 'Y5_NOTIN' \n" +
" \telse 'N_ELSE' \n" +
" end";
parsedClause = SimpleSyntaxParser.parse(condition);
helper = new CaseWhenElDataCalcHelper(parsedClause.getAst().get(0));
rawData = new HashMap<>();
rawData.put("is_sx_emp", "N");
rawData.put("or_emp", "Y");
Assert.assertEquals("case..when..中解析字段信息不正确",
8, parsedClause.getIdMapping().size());
Assert.assertEquals("case..when..in解析结果错误",
"Y2_OR",
helper.calcCaseWhenData(rawData)); rawData = new HashMap<>();
rawData.put("is_sx_emp", "N");
// rawData.put("or_emp", "Y");
rawData.put("or_emp2", "2");
Assert.assertEquals("case..when..or>2解析结果错误",
"Y5_NOTIN",
helper.calcCaseWhenData(rawData)); rawData = new HashMap<>();
rawData.put("is_sx_emp", "N");
// rawData.put("or_emp", "Y");
rawData.put("or_emp2", "2");
rawData.put("promotion_role_chn", "10");
Assert.assertEquals("case..when..notin解析结果错误",
"N_ELSE",
helper.calcCaseWhenData(rawData)); condition = " case \n" +
" \twhen (is_sx_emp='Y' or a_field=3) then 'Y1' \n" +
" \telse 'N_ELSE' \n" +
" end";
parsedClause = SimpleSyntaxParser.parse(condition);
helper = new CaseWhenElDataCalcHelper(parsedClause.getAst().get(0));
rawData = new HashMap<>();
rawData.put("is_sx_emp", "N");
rawData.put("or_emp", "Y");
Assert.assertEquals("case..when..中解析字段信息不正确",
2, parsedClause.getIdMapping().size());
Assert.assertEquals("case..when..()号解析结果错误",
"N_ELSE",
helper.calcCaseWhenData(rawData)); rawData = new HashMap<>();
rawData.put("is_sx_emp", "Y");
rawData.put("or_emp", "Y");
Assert.assertEquals("case..when..中解析字段信息不正确",
2, parsedClause.getIdMapping().size());
Assert.assertEquals("case..when..()号解析结果错误2",
"Y1",
helper.calcCaseWhenData(rawData)); }
}

  如果有更多场景,我们只需添加测试,然后完善相应逻辑即可。这里所有的测试,都可以基于sql协议进行,如有空缺则应弥补相应功能,而非要求用户按自己的标准来,毕竟标准是个好东西。

4. 更多表达式计算

  实际上,对表达式计算这东西,我们也许不一定非要自己去实现。毕竟太费力。有开源产品支持的,比如:aviator: https://www.oschina.net/p/aviator?hmsr=aladdin1e1    https://www.jianshu.com/p/02403dd1f4c4

  如果该语法不支持,则可以先转换成支持的语法,再使用其引擎计算即可。

  本质上,我们都是在做翻译工作!