业务保障部有一个需求,需要用hive实时计算上一小时的数据,比如现在是12点,我需要计算11点的数据,而且必须在1小时之后运行出来,但是他们用hive实现的时候发现就单个map任务运行都超过了1小时,根本没法满足需求,后来打电话让我帮忙优化一下,以下是优化过程:
1、hql语句:
CREATE TABLE weibo_mobile_nginx AS SELECT split(split(log, '`') [ 0 ], '\\|')[ 0 ] HOST, split(split(log, '`') [ 0 ], '\\|')[ 1 ] time, substr( split( split(split(log, '`') [ 2 ], '\\?')[ 0 ], ' ' )[ 0 ], 2 )request_type, split( split(split(log, '`') [ 2 ], '\\?')[ 0 ], ' ' )[ 1 ] interface, regexp_extract( log, ’.*& ua =[^ _ ]* __([^ _ ]*)__([^ _ ]*)__([^ _ ]*)__<span style="font-family: Arial, Helvetica, sans-serif;">[^&]*</span>’, 3 )version, regexp_extract( log, ’.*& ua =[^ _ ]* __([^ _ ]*)__([^ _ ]*)__([^ _ ]*)__.* ',1) systerm,regexp_extract(log,’.*&networktype=([^&%]*).*', 1 )net_type, split(log, '`')[ 4 ] STATUS, split(log, '`')[ 5 ] client_ip, split(log, '`')[ 6 ] uid, split(log, '`')[ 8 ] request_time, split(log, '`')[ 12 ] request_uid, split(log, '`')[ 13 ] http_host, split(log, '`')[ 15 ] upstream_response_time, split(log, '`')[ 16 ] idc FROM ods_wls_wap_base_orig WHERE dt = '20150311' AND HOUR = '08' AND( split(log, '`')[ 13 ]= 'api.weibo.cn' OR split(log, '`')[ 13 ]= 'mapi.weibo.cn’);
其实这个hql很简单,从一个只有一列数据的表ods_wls_wap_base_orig中获取数据,然后对每一行数据进行split或者正则表达式匹配得到需要的字段信息,最后通过输出的数据创建weibo_mobile_nginx表。
其中表ods_wls_wap_base_orig的一行数据格式如下:
web043.mweibo.yhg.sinanode.com|[11/Mar/2015:00:00:01 +0800]`-`"GET /2/remind/unread_count?v_f=2&c=android&wm=9847_0002&remind_version=0&with_settings=1&unread_message=1&from=1051195010&lang=zh_CN&skin=default&with_page_group=1&i=4acbdd0&s=6b2cd11c&gsid=4uQ15a2b3&ext_all=0&idc=&ua=OPPO-R8007__weibo__5.1.1__android__android4.3&oldwm=9893_0028
HTTP/1.1"`"R8007_4.3_weibo_5.1.1_android"`200`[121.60.78.23]`3226234350`"-"`0.063`351`-`121.60.78.23`1002792675011956002`api.weibo.cn`-`0.063`yhg
20150311 00
只有1列,列名是log。
2、既然hql实现很慢,我第一次优化的尝试就是写mapreduce
map代码如下:
public class Map extends Mapper<LongWritable, Text, Text, Text> { private Text outputKey = new Text(); private Text outputValue = new Text(); Pattern p_per_client = Pattern .compile(".*&ua=[^_]*__([^_]*)__([^_]*)__([^_]*)__[^&]*"); Pattern net_type_parent = Pattern.compile(".*&networktype=([^&%]*).*"); public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException { String[] arr = value.toString().split("`"); if (arr[13].equals("api.weibo.cn") || arr[13].equals("mapi.weibo.cn")) { Matcher matcher = p_per_client.matcher(value.toString()); String host = ""; String time = ""; String request_type = ""; String interface_url = ""; String version = ""; String systerm = ""; String net_type = ""; String status = ""; String client_ip = ""; String uid = ""; String request_time = "0"; String request_uid = ""; String http_host = ""; String upstream_response_time = "0"; String idc = ""; host = arr[0].split("\\|")[0]; time = arr[0].split("\\|")[1]; request_type = arr[2].split("\\?")[0].split(" ")[0].substring(1); interface_url = arr[2].split("\\?")[0].split(" ")[1]; if (matcher.find()) { version = matcher.group(1); systerm = matcher.group(2); } Matcher matcher_net = net_type_parent.matcher(value.toString()); if (matcher_net.find()) { net_type = matcher_net.group(1); } status = arr[4]; client_ip = arr[5]; uid = arr[6]; if (!arr[8].equals("-")) { request_time = arr[8]; } request_uid = arr[12]; http_host = arr[13]; if (!arr[15].equals("-")) { upstream_response_time = arr[15]; } idc = arr[16]; outputKey.set(host + "\t" + time + "\t" + request_type + "\t" + interface_url + "\t" + version + "\t" + systerm + "\t" + net_type + "\t" + status + "\t" + client_ip + "\t" + uid + "\t" + request_uid + "\t" + http_host + "\t" + idc); outputValue.set(request_time + "\t" + upstream_response_time); context.write(outputKey, outputValue); } }
java代码其实也很简单,这里不多说。打包提交job,结果map最慢的运行了40分钟,平均map运行时间达到30分钟,虽然整个job在1小时内完成了,但是也很慢,这个问题看来不是用java改写就能好的问题。
3、最后检测正则表达式
改用java实现的mapreduce运行也很慢,看来问题还是其他原因,我看了一下hql中的正则表达式,修改了几个地方:
原来的:
regexp_extract( log, ’.*& ua =[^ _ ]* __([^ _ ]*)__([^ _ ]*)__([^ _ ]*)__[^&]*’, 3 )version, regexp_extract( log, ’.*& ua =[^ _ ]* __([^ _ ]*)__([^ _ ]*)__([^ _ ]*)__.* ',1) systerm, regexp_extract(log,’.*&networktype=([^&%]*).*', 1 )net_type,
修改后:
regexp_extract( log, '&ua=[^_]*__[^_]*__([^_]*)__[^_]*__', 1 )version, regexp_extract( log, '&ua=[^_]*__[^_]*__[^_]*__([^_]*)__', 1 )systerm, regexp_extract( log, '&networktype=([^&%]*)', 1 )net_type,
其实匹配目标很明确,所以我把正则表达式前后的".*"去掉了,同时去掉了没必要的group,索引都改成了1。
java代码的正则表达式也进行了修改:
Pattern p_per_client = Pattern .compile("&ua=[^_]*__[^_]*__([^_]*)__([^_]*)__"); Pattern net_type_parent = Pattern.compile("&networktype=([^&%]*).");
分别提交测试了一下,速度ss的,修改后的hql和mapreduce整个作业6分钟运行完成,平均map运行时间2分钟,速度提升很大,满足了他们的速度要求。
总结:
1、正则表达式最前面包含“.*”,这样在匹配的时候需要从第一个字符开始匹配,速度非常非常慢,如果我们匹配的目标很明确的情况下,应该去掉“.*”
2、以后遇到这种问题的时候,一定要看看正则表达式是不是写得有问题,切记切记。