在正则表达式中使用变量

Question

我正在使用一些sub(), gsub()函数来替换存储在变量中的内容。

比如说：

$ awk 'BEGIN {str="hello bee"; patt="llo"; gsub(patt,"XX",str); print str}'
heXX bee

这将str所有llo XX中包含的字符串替换为"he"。好的。

现在说我想使用一个使用变量和模式的更复杂的正则表达式。例如，patt +变量gsub(/he/patt, ...)。我该怎么办？

如果我尝试awk 'BEGIN {str="hello bee"; patt="llo"; gsub(/he/patt,"XX",str); print str}' ，它就无法运作：

hello bee

返回

XX bee

而不是

15/09/30 17:57:21 ERROR shuffle.OneForOneBlockFetcher: Failed while starting block fetches
java.lang.RuntimeException: java.lang.IllegalArgumentException: Size exceeds Integer.MAX_VALUE
at sun.nio.ch.FileChannelImpl.map(FileChannelImpl.java:836)
at org.apache.spark.storage.DiskStore$$anonfun$getBytes$2.apply(DiskStore.scala:125)
at org.apache.spark.storage.DiskStore$$anonfun$getBytes$2.apply(DiskStore.scala:113)
at org.apache.spark.util.Utils$.tryWithSafeFinally(Utils.scala:1206)
at org.apache.spark.storage.DiskStore.getBytes(DiskStore.scala:127)
at org.apache.spark.storage.DiskStore.getBytes(DiskStore.scala:134)
at org.apache.spark.storage.BlockManager.doGetLocal(BlockManager.scala:512)
at org.apache.spark.storage.BlockManager.getBlockData(BlockManager.scala:302)
at org.apache.spark.network.netty.NettyBlockRpcServer$$anonfun$2.apply(NettyBlockRpcServer.scala:57)
at org.apache.spark.network.netty.NettyBlockRpcServer$$anonfun$2.apply(NettyBlockRpcServer.scala:57)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:244)
at scala.collection.IndexedSeqOptimized$class.foreach(IndexedSeqOptimized.scala:33)
at scala.collection.mutable.ArrayOps$ofRef.foreach(ArrayOps.scala:108)
at scala.collection.TraversableLike$class.map(TraversableLike.scala:244)
at scala.collection.mutable.ArrayOps$ofRef.map(ArrayOps.scala:108)
at org.apache.spark.network.netty.NettyBlockRpcServer.receive(NettyBlockRpcServer.scala:57)
at org.apache.spark.network.server.TransportRequestHandler.processRpcRequest(TransportRequestHandler.java:114)
at org.apache.spark.network.server.TransportRequestHandler.handle(TransportRequestHandler.java:87)
at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:101)
at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:51)
at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
at io.netty.handler.timeout.IdleStateHandler.channelRead(IdleStateHandler.java:266)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:103)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
at io.netty.handler.codec.ByteToMessageDecoder.channelRead(ByteToMessageDecoder.java:244)
at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:308)
at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:294)
at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:846)
at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131)
at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:511)
at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:468)
at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:382)
at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:354)
at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:111)
at java.lang.Thread.run(Thread.java:745)

at org.apache.spark.network.client.TransportResponseHandler.handle(TransportResponseHandler.java:162)
at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:103)
at org.apache.spark.network.server.TransportChannelHandler.channelRead0(TransportChannelHandler.java:51)
at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105)

Answer 1

当你需要字符串连接时，必须使用字符串分隔符而不是正则表达式的regexp分隔符：

$ awk 'BEGIN {str="hello bee"; patt="llo"; gsub("he"patt,"XX",str); print str}'
XX bee

请注意，然后你需要加倍任何转义字符，因为awk必须首先将字符串转换为regexp，这样才能使用其中一个转义字符。

Answer 2

你可以这样做：

/he/patt

"he" patt并没有将字符串连接起来，ThingCodec会这样做。

Answer 3

这将起作用

awk 'BEGIN {str="hello bee"; patt="llo"; gsub("he" patt,"XX",str); print str}'
XX bee

基本上你必须将整个模式定义为一个变量，而不是它的一部分。