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提高微服务可用性的中间件CoralCache,针对这个问题,这篇文章详细介绍了相对应的分析和解答,希望可以帮助更多想解决这个问题的小伙伴找到更简单易行的方法。
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当数据库出问题时能降级从本地缓存的数据中查询数据, CoralCache就是这样一个提高微服务可用性的中间件。
有些场景下,微服务依赖数据库中一些配置项或者数量很少的数据,但当数据库本身有问题时候,即使数据量很少,这个服务是不能正常工作;因此需要考虑一种能支持全量+极少变更的全局数据的场景,当数据库出问题时能降级从本地缓存的数据中查询数据,CoralCache就是这样一个提高微服务可用性的中间件。
CoralCache中间件架构如下图所示,通过@EnableLocal注解开启功能,应用启动后将配置的表数据一次性加载到内存中,内存中的数据逻辑结构和数据库中的逻辑结构一样。
图1. 架构图
内存查询引擎的原理是数据库查询降级发生后,Intercepter将拦截到的原始SQL传入查询引擎中,查询引擎解析SQL后得到表名、列名、where条件表达式,遍历InnerDB中对应表的数据行,并通过表达式计算引擎计算结果,计算结果为真则添加到结果集中最后返回给调用方。
计算引擎结构如下图所示,将where条件表达式转为后缀表达式后依次遍历后缀表达式,遇到操作数直接入栈,遇到操作符则根据操作符需要的操作数个数弹栈。
图2. 表达式计算引擎结构
然后根据操作符和弹出的操作数进行计算,不同操作符对应不同的计算方法,并将计算后的结果重新作为操作数入栈执到遍历完成,核心计算流程代码如下所示:
public Object calc(Expression where, InnerTable table, InnerRow row) { try { postTraversal(where); } catch (Exception e) { log.warn("calc error: {}", e.getMessage()); return false; } for (ExprObj obj : exprList) { switch (obj.exprType()) { case ITEM: stack.push(obj); break; case BINARY_OP: { ExprObj result = calcBinaryOperation(((ExprOperation) obj).getOperationType(), table, row); stack.push(result); break; } case UNARY_OP: { ExprObj result = calcSingleOperation(((ExprOperation) obj).getOperationType(), table, row); stack.push(result); break; } case FUNCTION_OP: { ExprObj result = calcFunctionOperation(((ExprOperation) obj).getOperationType(), table, row); stack.push(result); break; } default: break; } } return stack.pop(); }
逻辑常见运算符为<、<=、>、>=、=等,它们的共性都是需要2个操作数并且返回值是布尔类型。
public ExprItem logicalCalculus(InnerTable table, InnerRow row, LogicalOperation logicalOperation) { ExprObj second = stack.pop(); ExprObj first = stack.pop(); ExprItem result = new ExprItem(); result.setItemType(ItemType.T_CONST_OBJ); Obj firstObj = getObj((ExprItem) first, table, row); Obj secondObj = getObj((ExprItem) second, table, row); boolean value = logicalOperation.apply(firstObj, secondObj); result.setValue(new Obj(value, ObjType.BOOL)); return result; }
例子,以"="的实现来展示:
private ExprObj calcBinaryOperation(OperationType type, InnerTable table, InnerRow row) { ExprObj result = null; switch (type) { case T_OP_EQ: result = logicalCalculus(table, row, (a, b) -> ObjUtil.eq(a, b)); // 等于符号的实现 break; ... default: break; } return result; } public class ObjUtil { private static ObjType resultType(ObjType first, ObjType second) { return ObjType.RESULT_TYPE[first.ordinal()][second.ordinal()]; } public static boolean eq(Obj first, Obj second) { ObjType type = resultType(first.getType(), second.getType()); switch (type) { case LONG: { long firstValue = first.getValueAsLong(); long secondValue = second.getValueAsLong(); return firstValue == secondValue; } case DOUBLE: { double firstValue = first.getValueAsDouble(); double secondValue = second.getValueAsDouble(); return Double.compare(firstValue, secondValue) == 0; } case TIMESTAMP: { java.util.Date firstValue = first.getValueAsDate(); java.util.Date secondValue = first.getValueAsDate(); return firstValue.compareTo(secondValue) == 0; } ... default: break; } throw new UnsupportedOperationException(first.getType() + " and " + second.getType() + " not support '=' operation."); } }
数学运算和逻辑运算的流程都一样,只不过运算后的结果为数字类型。
除了上面说的逻辑运算和数学运算外,还支持进行模糊匹配的特殊操作符LIKE。
常见用法如下
LIKE "%HUAWEI" 匹配以HUAWEI结尾的字符串
LIKE "HUAWEI%" 匹配以HUAWEI开头的字符串
LIKE "A_B" 匹配以"A"起头且以"Z"为结尾的字串
LIKE "A?B" 同上
LIKE "%[0-9]%" 匹配含有数字的字符串
LIKE "%[a-z]%" 匹配含有小写字母字符串
LIKE "%[!0-9]%"匹配不含数字的字符串
?和_都表示单个字符
JAVA中实现LIKE的方案:将LIKE的模式转为JAVA中的正则表达式。
expr := wild-card + expr | wild-char + expr | escape + expr | string + expr | "" wild-card := % wild-char := _ escape := [%|_] string := [^%_]+ (One or > more characters that are not wild-card or wild-char)
public abstract class Token { private final String value; public Token(String value) { this.value = value; } public abstract String convert(); public String getValue() { return value; } } public class ConstantToken extends Token { public ConstantToken(String value) { super(value); } @Override public String convert() { return getValue(); } } public class EscapeToken extends Token { public EscapeToken(String value) { super(value); } @Override public String convert() { return getValue(); } } public class StringToken extends Token { public StringToken(String value) { super(value); } @Override public String convert() { return Pattern.quote(getValue()); } } public class WildcardToken extends Token { public WildcardToken(String value) { super(value); } @Override public String convert() { return ".*"; } } public class WildcharToken extends Token { public WildcharToken(String value) { super(value); } @Override public String convert() { return "."; } }
public class Tokenizer { private Collectionpatterns = new LinkedList<>(); public Tokenizer add(String regex, Function creator) { this.patterns.add(new Tuple >(Pattern.compile(regex), creator)); return this; } public Collection tokenize(String clause) throws RuntimeException { Collection tokens = new ArrayList<>(); String copy = String.copyValueOf(clause.toCharArray()); int position = 0; while (!copy.equals("")) { boolean found = false; for (Tuple tuple : this.patterns) { Pattern pattern = (Pattern) tuple.getFirst(); Matcher m = pattern.matcher(copy); if (m.find()) { found = true; String token = m.group(1); Function fn = (Function ) tuple.getSecond(); tokens.add(fn.apply(token)); copy = m.replaceFirst(""); position += token.length(); break; } } if (!found) { throw new RuntimeException("Unexpected sequence found in input string, at " + position); } } return tokens; } }
public class LikeTranspiler { private static Tokenizer TOKENIZER = new Tokenizer() .add("^(\\[[^]]*])", ConstantToken::new) .add("^(%)", WildcardToken::new) .add("^(_)", WildcharToken::new) .add("^([^\\[\\]%_]+)", StringToken::new); public static String toRegEx(String pattern) throws ParseException { StringBuilder sb = new StringBuilder().append("^"); for (Token token : TOKENIZER.tokenize(pattern)) { sb.append(token.convert()); } return sb.append("$").toString(); } }
直接调用LikeTranspiler的toRegEx方法将LIKE语法转为JAVA中的正则表达式。
private ExprObj calcBinaryOperation(OperationType type, InnerTable table, InnerRow row) { ExprObj result = null; switch (type) { . . . case T_OP_LIKE: result = logicalCalculus(table, row, (a, b) -> ObjUtil.like(a, b)); break; . . . } return result; } public static boolean like(Obj first, Obj second) { Assert.state(first.getType() == ObjType.STRING, OperationType.T_OP_LIKE + " only support STRING."); Assert.state(second.getType() == ObjType.STRING, OperationType.T_OP_LIKE + " only support STRING."); String firstValue = (String) first.getRelValue(); String secondValue = (String) second.getRelValue(); String regEx = LikeTranspiler.toRegEx(secondValue); return Pattern.compile(regEx).matcher(firstValue).matches(); }
通过创建词法分析器并使用此方法进行转换,我们可以防止LIKE像这样的子句被转换为正则表达式%abc[%]%,该子句应将其中的任何子字符串与其中的子字符串匹配,该子句将与子字符串或匹配任何字符串。abc%.abc[.].abc.abc。
不同数据类型在进行计算时需要转型,具体的转化入下二维数组中。
// 不同类型计算后的类型 ObjType[][] RESULT_TYPE = { //UNKNOWN BYTE SHORT INT LONG FLOAT DOUBLE DECIMAL BOOL DATE TIME TIMESTAMP STRING NULL { UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN },// UNKNOWN { UNKNOWN, LONG, LONG, LONG, LONG, DOUBLE, DOUBLE, DECIMAL, BOOL, UNKNOWN, UNKNOWN, UNKNOWN, LONG, UNKNOWN },// BYTE { UNKNOWN, LONG, LONG, LONG, LONG, DOUBLE, DOUBLE, DECIMAL, BOOL, UNKNOWN, UNKNOWN, UNKNOWN, LONG, UNKNOWN },// SHORT { UNKNOWN, LONG, LONG, LONG, LONG, DOUBLE, DOUBLE, DECIMAL, BOOL, UNKNOWN, UNKNOWN, UNKNOWN, LONG, UNKNOWN },// INT { UNKNOWN, LONG, LONG, LONG, LONG, DOUBLE, DOUBLE, DECIMAL, BOOL, UNKNOWN, UNKNOWN, UNKNOWN, LONG, UNKNOWN },// LONG { UNKNOWN, DOUBLE, DOUBLE, DOUBLE, DOUBLE, DOUBLE, DOUBLE, DECIMAL, BOOL, UNKNOWN, UNKNOWN, UNKNOWN, DOUBLE, UNKNOWN },// FLOAT { UNKNOWN, DOUBLE, DOUBLE, DOUBLE, DOUBLE, DOUBLE, DOUBLE, DECIMAL, BOOL, UNKNOWN, UNKNOWN, UNKNOWN, DOUBLE, UNKNOWN },// DOUBLE { UNKNOWN, DECIMAL, DECIMAL, DECIMAL, DECIMAL, DECIMAL, DECIMAL, DECIMAL, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, DECIMAL, UNKNOWN },// DECIMAL { UNKNOWN, BOOL, BOOL, BOOL, BOOL, BOOL, BOOL, BOOL, BOOL, UNKNOWN, UNKNOWN, UNKNOWN, BOOL, UNKNOWN },// BOOL { UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, TIMESTAMP, TIMESTAMP, TIMESTAMP, TIMESTAMP, UNKNOWN },// DATE { UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, TIMESTAMP, TIMESTAMP, TIMESTAMP, TIMESTAMP, UNKNOWN },// TIME { UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, TIMESTAMP, TIMESTAMP, TIMESTAMP, TIMESTAMP, UNKNOWN },// TIMESTAMP { UNKNOWN, LONG, LONG, LONG, LONG, DOUBLE, DOUBLE, DECIMAL, BOOL, TIMESTAMP, TIMESTAMP, TIMESTAMP, STRING, UNKNOWN },// STRING { UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN, UNKNOWN },// NULL };
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