µ±ÄúÐèÒª´¦Àí´óÁ¿Êý¾Ýʱ£¬´æ´¢ËüÃÇÊÇÒ»¸ö²»´íµÄÑ¡Ôñ¡£ÁîÈËÄÑÒÔÖÃÐŵķ¢ÏÖ»òδÀ´Ô¤²â²»»áÀ´×ÔδʹÓõÄÊý¾Ý¡£´óÊý¾ÝÊÇÒ»¸ö¸´ÔӵĹÖÊÞ¡£ÓÃ
Java? ±à³ÌÓïÑÔ±àд¸´Ô MapReduce ³ÌÐòÒªºÄ·ÑºÜ¶àʱ¼ä¡¢Á¼ºÃµÄ×ÊÔ´ºÍרҵ֪ʶ£¬ÕâÕýÊÇ´ó²¿·ÖÆóÒµËù²»¾ß±¸µÄ¡£ÕâÒ²ÊÇÔÚ
Hadoop ÉÏʹÓÃÖîÈç Hive Ö®ÀàµÄ¹¤¾ß¹¹½¨Êý¾Ý¿â»á³ÉΪһ¸ö¹¦ÄÜÇ¿´óµÄ½â¾ö·½°¸µÄÔÒò¡£
Èç¹ûÒ»¼Ò¹«Ë¾Ã»ÓÐ×ÊÔ´¹¹½¨Ò»¸ö¸´ÔӵĴóÊý¾Ý·ÖÎöƽ̨£¬¸ÃÔõô°ì£¿µ±ÒµÎñÖÇÄÜ (BI)¡¢Êý¾Ý²Ö¿âºÍ·ÖÎö¹¤¾ßÎÞ·¨Á¬½Óµ½
Apache Hadoop ϵͳ£¬»òÕßËüÃDZÈÐèÇó¸ü¸´ÔÓʱ£¬ÓÖ¸ÃÔõÑù°ì£¿´ó¶àÊýÆóÒµ¶¼ÓÐһЩӵÓйØÏµÊý¾Ý¿â¹ÜÀíϵͳ
(RDBMSes) ºÍ½á¹¹»¯²éѯÓïÑÔ (SQL) ¾ÑéµÄÔ±¹¤¡£Apache Hive ÔÊÐíÕâЩÊý¾Ý¿â¿ª·¢ÈËÔ±»òÕßÊý¾Ý·ÖÎöÈËԱʹÓÃ
Hadoop£¬ÎÞÐèÁ˽â Java ±à³ÌÓïÑÔ»òÕß MapReduce¡£ÏÖÔÚ£¬Äú¿ÉÒÔÉè¼ÆÐÇÐÍÄ£Ð͵ÄÊý¾Ý²Ö¿â£¬»òÕß³£Ì¬»¯µÄÊý¾Ý¿â£¬¶ø²»ÐèÒªÌôÕ½
MapReduce ´úÂë¡£ºöȻ֮¼ä£¬BI ºÍ·ÖÎö¹¤¾ß£¬±ÈÈç IBM Cognos? »òÕß SPSS? Statistics£¬¾Í¿ÉÒÔÁ¬½Óµ½
Hadoop ϵͳ¡£
Êý¾Ý¿â
¹¹½¨Êý¾Ý¿â£¬²¢ÇÒÄܹ»Ê¹ÓÃÕâЩÊý¾Ý£¬Õâ²»ÊÇ Hadoop »òÕßÊý¾Ý¿âÎÊÌâ¡£¶àÄêÒÔÀ´£¬ÈËÃÇһֱϰ¹ß½«Êý¾Ý×éÖ¯µ½¿âÖС£ÓÐÐí¶àÓÉÀ´ÒѾõÄÎÊÌ⣺ÈçºÎ½«Êý¾Ý·ÖÃűðÀࣿÈçºÎ½«ËùÓÐÊý¾ÝÁ¬½Óµ½¼¯³ÉµÄƽ̨¡¢»úÏä»òÕß
¿â£¿¶àÄêÀ´£¬¸÷ÖÖ·½°¸²ã³ö²»Çî¡£
ÈËÃÇ·¢Ã÷Á˺ܶ෽·¨£¬±ÈÈç Dewey Decimal ϵͳ¡£ËûÃǽ«Í¨Ñ¶Â¼ÖеÄÈËÃû»òÆóÒµÃû°´ÕÕ×Öĸ˳ÐòÅÅÁС£»¹ÓнðÊôÎļþ¹ñ¡¢´ø»õ¼ÜµÄ²Ö¿â¡¢µØÖ·¿¨Îļþϵͳ£¬µÈµÈ¡£¹ÍÖ÷³¢ÊÔÓÃʱ¼ä¿¨£¬´ò¿¨Æ÷ÒÔ¼°Ê±¼ä±í×·×ÙÔ±¹¤¡£ÈËÃÇÐèÒª½á¹¹»¯ºÍ×éÖ¯»¯Êý¾Ý£¬»¹ÐèÒª·´Ó³ºÍ¼ì²éÕâЩÊý¾Ý¡£Èç¹ûÄúÎÞ·¨·ÃÎÊ¡¢½á¹¹»¯»òÀí½âÕâЩÊý¾Ý£¬ÄÇô´æ´¢Õâô¶àµÄÊý¾ÝÓÐʲôʵ¼ÊÒâÒåÄØ£¿
RDBMSes ʹÓÃÁ˹ý¼¯ºÏÂۺ͵ÚÈý·¶Ê½¡£Êý¾Ý²Ö¿âÓÐ Kimball¡¢Inmon¡¢ÐÇÐÍÄ£ÐÍ¡¢Corporate
Information Factory£¬ÒÔ¼°×¨ÓÃÊý¾Ý¼¯ÊС£ËûÃÇÓÐÖ÷Êý¾Ý¹ÜÀí¡¢ÆóÒµ×ÊÔ´¹æ»®¡¢¿Í»§¹ØÏµ¹ÜÀí¡¢µç×ÓÒ½ÁƼǼºÍÆäËûÐí¶àϵͳ£¬ÈËÃÇʹÓÃÕâЩϵͳ½«ÊÂÎñ×éÖ¯µ½Ä³ÖֽṹºÍÖ÷ÌâÖС£ÏÖÔÚ£¬ÎÒÃÇÓдóÁ¿À´×Ô¸÷¸öÐÐÒµµÄ·Ç»ú¹¹»¯»ò°ë½á¹¹»¯Êý¾Ý£¬ÀýÈ磬É罻ýÌå¡¢Óʼþ¡¢Í¨»°¼Ç¼¡¢»úеָÁî¡¢Ô¶³ÌÐÅÏ¢£¬µÈµÈ¡£ÕâЩÐÂÊý¾ÝÐèÒª¼¯³Éµ½´æ´¢½á¹¹»¯µÄоÉÊý¾ÝµÄ·Ç³£¸´ÔÓ¡¢·Ç³£ÅÓ´óµÄϵͳÖС£ÈçºÎ·ÖÀà²ÅÄÜʹµÃÏúÊÛ¾ÀíÄܹ»¸Ä½ø±¨¸æ£¿ÈçºÎ¹¹½¨¿â²ÅÄÜʹµÃÖ´ÐÐÖ÷¹ÜÄܹ»·ÃÎÊͼ±íºÍͼÐΣ¿
ÄúÐèÒªÕÒµ½Ò»ÖÖ½«Êý¾Ý½á¹¹»¯µ½Êý¾Ý¿âµÄ·½·¨¡£·ñÔò£¬Ö»ÊÇÓµÓдóÁ¿Ö»ÓÐÊý¾Ý¿ÆÑ§¼Ò²ÅÄÜ·ÃÎÊÊý¾Ý¡£ÓÐʱ£¬ÈËÃÇÖ»ÊÇÐèÒª¼òµ¥µÄ±¨¸æ¡£ÓÐʱ£¬ËûÃÇÖ»ÊÇÏëÒªÍÏ×§»òÕß±àд
SQL ²éѯ¡£
´óÊý¾Ý¡¢Hadoop ºÍ InfoSphere BigInsights
±¾Ð¡½Ú½«ÏòÄú½éÉÜ InfoSphere? BigInsights?£¬ÒÔ¼°ËüÓë Hadoop¡¢´óÊý¾Ý¡¢Hive¡¢Êý¾Ý¿âµÈÓкÎÁªÏµ¡£InfoSphere
BigInsights ÊÇ Hadoop µÄ IBM ·ÖÇø¡£Äú¿ÉÄÜ¶Ô Apache ºÍ Cloudera
±È½ÏÁ˽⣬µ«ÊÇÒµÄÚÐí¶àÈ˶¼ÔøÉæ×ã Hadoop¡£Ëü¿ªÊ¼ÓÚ¿ªÔ´µÄʹÓà MapReduce µÄ Hadoop
ºÍ Hadoop ·Ö²¼Ê½Îļþϵͳ (HDFS)£¬Í¨³£»¹°üÀ¨ÆäËû¹¤¾ß£¬±ÈÈç ZooKeeper¡¢Oozie¡¢Sqoop¡¢Hive¡¢Pig
ºÍ HBase¡£ÕâЩ·¢²¼°æÓëÆÕͨ Hadoop µÄÇø±ðÔÚÓÚËüÃDZ»Ìí¼ÓÔÚ Hadoop ¶¥²ã¡£InfoSphere
BigInsights ¾ÍÊôÓÚÕâÒ»Àà°æ±¾¡£
Äú¿ÉÒÔÔÚ Hadoop µÄ Cloudera °æ±¾Ö®ÉÏʹÓà InfoSphere BigInsights¡£´ËÍ⣬InfoSphere
BigInsights Ìṩһ¸ö¿ìËٵķǽṹ»¯µÄ·ÖÎöÒýÇæ£¬Äú¿ÉÒÔ½«ËüºÍ InfoSphere Streams
½áºÏÔÚÒ»ÆðʹÓá£InfoSphere Streams ÊÇÒ»¸öʵʱµÄ·ÖÎöÒýÇæ£¬Ëü¿ª´´ÁËÁªºÏʵʱ·ÖÎöºÍÃæÏòÅú´ÎµÄ·ÖÎöµÄ¿ÉÄÜ¡£
InfoSphere BigInsights »¹ÓµÓÐÄÚÖõġ¢»ùÓÚä¯ÀÀÆ÷µÄµç×Ó±í¸ñ BigSheets¡£Õâ¸öµç×Ó±í¸ñÔÊÐí·ÖÎöÈËԱÿÌìÒÔµç×Ó±í¸ñÑùʽʹÓôóÊý¾ÝºÍ
Hadoop¡£ÆäËû¹¦ÄܰüÀ¨»ùÓÚ½ÇÉ«µÄ°²È«ºÍ¹ÜÀíµÄ LDAP ¼¯³É£»Óë InfoSphere DataStage?
µÄ¼¯³É£¬ÓÃÓÚÌáÈ¡¡¢×ª»»¡¢¼ÓÔØ (ETL)£»³£ÓõÄʹÓð¸ÀýµÄ¼ÓËÙÆ÷£¬±ÈÈçÈÕÖ¾ºÍ»úÆ÷Êý¾Ý·ÖÎö£»°üº¬³£ÓÃĿ¼ºÍ¿ÉÖØ¸´Ê¹Óù¤×÷µÄÓ¦ÓÃĿ¼£»Eclipse
²å¼þ£»ÒÔ¼° BigIndex£¬Ëüʵ¼ÊÉÏÊÇÒ»¸ö»ùÓÚ Lucene µÄË÷Òý¹¤¾ß£¬¹¹½¨ÓÚ Hadoop Ö®ÉÏ¡£
Äú»¹¿ÉÒÔʹÓà Adaptive MapReduce¡¢Ñ¹ËõÎı¾Îļþ¡¢×ÔÊÊÓ¦µ÷¶ÈÔöÇ¿À´Ìá¸ßÐÔÄÜ¡£´ËÍ⣬Äú»¹¿ÉÒÔ¼¯³ÉÆäËûÓ¦Óã¬ÀýÈ磬ÄÚÈÝ·ÖÎöºÍ
Cognos Consumer Insights¡£
Hive
Hive ÊÇÒ»¸öÇ¿´óµÄ¹¤¾ß¡£ËüʹÓÃÁË HDFS£¬ÔªÊý¾Ý´æ´¢£¨Ä¬ÈÏÇé¿öÏÂÊÇÒ»¸ö Apache Derby
Êý¾Ý¿â£©¡¢shell ÃüÁî¡¢Çý¶¯Æ÷¡¢±àÒëÆ÷ºÍÖ´ÐÐÒýÇæ¡£Ëü»¹Ö§³Ö Java Êý¾Ý¿âÁ¬½ÓÐÔ (JDBC) Á¬½Ó¡£
ÓÉÓÚÆäÀàËÆ SQL µÄÄÜÁ¦ºÍÀàËÆÊý¾Ý¿âµÄ¹¦ÄÜ£¬Hive Äܹ»Îª·Ç±à³ÌÈËÔ±´ò¿ª´óÊý¾Ý Hadoop Éú̬ϵͳ¡£Ëü»¹ÌṩÁËÍⲿ
BI Èí¼þ£¬ÀýÈ磬ͨ¹ý JDBC Çý¶¯Æ÷ºÍ Web ¿Í»§¶ËºÍ Cognos Á¬½Ó¡£
Äú¿ÉÒÔÒÀ¿¿ÏÖÓеÄÊý¾Ý¿â¿ª·¢ÈËÔ±£¬²»Ó÷Ñʱ·ÑÁ¦µØÑ°ÕÒ Java MapReduce ±à³ÌÈËÔ±¡£ÕâÑù×öµÄºÃ´¦ÔÚÓÚ£ºÄú¿ÉÒÔÈÃÒ»¸öÊý¾Ý¿â¿ª·¢ÈËÔ±±àд
10-15 ÐÐ SQL ´úÂ룬Ȼºó½«ËüÓÅ»¯ºÍ·ÒëΪ MapReduce ´úÂ룬¶ø²»ÊÇÇ¿ÆÈÒ»¸ö·Ç±à³ÌÈËÔ±»òÕß±à³ÌÈËԱд
200 ÐдúÂ룬ÉõÖÁ¸ü¶àµÄ¸´ÔÓ MapReduce ´úÂë¡£
Hive ³£±»ÃèÊöΪ¹¹½¨ÓÚ Hadoop Ö®ÉϵÄÊý¾Ý²Ö¿â»ù´¡¼Ü¹¹¡£ÊÂʵÊÇ£¬Hive ÓëÊý¾Ý²Ö¿âûÓÐʲô¹ØÏµ¡£Èç¹ûÄúÏë¹¹½¨Ò»¸öÕæÊµµÄÊý¾Ý²Ö¿â£¬¿ÉÒÔ½èÖúһЩ¹¤¾ß£¬±ÈÈç
IBM Netezza¡£µ«ÊÇÈç¹ûÄúÏëʹÓà Hadoop ¹¹½¨Ò»¸öÊý¾Ý¿â£¬µ«ÓÖûÓÐÕÆÎÕ Java »òÕß MapReduce
·½ÃæµÄ֪ʶ£¬ÄÇô Hive »áÊÇÒ»¸ö·Ç³£²»´íµÄÑ¡Ôñ£¨Èç¹ûÄúÁ˽â SQL£©¡£Hive ÔÊÐíÄúʹÓà Hadoop
ºÍ HBase µÄ HiveQL ±àдÀàËÆ SQL µÄ²éѯ£¬»¹ÔÊÐíÄúÔÚ HDFS Ö®ÉϹ¹½¨ÐÇÐÍÄ£ÐÍ¡£
Hive Óë RDBMSes
Hive ÊÇÒ»¸ö¶Áģʽ ϵͳ£¬¶ø RDBMSes ÊÇÒ»¸öµäÐ͵Äдģʽ ϵͳ¡£´«Í³µÄ RDMBSes ÔÚ±àдÊý¾ÝʱÑé֤ģÐÍ¡£Èç¹ûÊý¾ÝÓë½á¹¹²»·û£¬Ôò»áÔâµ½¾Ü¾ø¡£Hive
²¢²»¹ØÐÄÊý¾ÝµÄ½á¹¹£¬ÖÁÉÙ²»»áÔÚµÚһʱ¼ä¹ØÐÄÊý¾Ý½á¹¹£¬Ëü²»»áÔÚÄú¼ÓÔØÊý¾ÝʱÑé֤ģÐÍ¡£¸üÈ·ÇеØËµ£¬Ö»ÔÚÄúÔËÐвéѯ֮ºó£¬Ëü²Å»á¹ØÐĸÃÄ£ÐÍ¡£
Hive µÄÏÞÖÆ
ÔÚʹÓà Hive ʱ¿ÉÄÜ»áÓÐһЩÌôÕ½¡£Ê×ÏÈ£¬ËüÓë SQL-92 ²»¼æÈÝ¡£Ä³Ð©±ê×¼µÄ SQL º¯Êý£¬ÀýÈç
NOT IN¡¢NOT LIKE ºÍ NOT EQUAL ²¢²»´æÔÚ£¬»òÕßÐèҪijÖÖ¹¤×÷Çø¡£ÀàËÆµØ£¬²¿·ÖÊýѧº¯ÊýÓÐÑϸñÏÞÖÆ£¬»òÕß²»´æÔÚ¡£Ê±¼ä´Á»òÕß
date ÊÇ×î½üÌí¼ÓµÄÖµ£¬Óë SQL ÈÕÆÚ¼æÈÝÐÔÏà±È£¬¸ü¾ßÓÐ Java ÈÕÆÚ¼æÈÝÐÔ¡£Ò»Ð©¼òµ¥¹¦ÄÜ£¬ÀýÈçÊý¾Ý²î±ð£¬²»ÄÜÕý³£¹¤×÷¡£
´ËÍ⣬Hive ²»ÊÇΪÁË»ñµÃµÍÑÓʱµÄ¡¢ÊµÊ±»òÕß½üºõʵʱµÄ²éѯ¶ø¿ª·¢µÄ¡£SQL ²éѯ±»×ª»¯³É MapReduce£¬ÕâÒâζ×ÅÓ봫ͳ
RDBMS Ïà±È£¬¶ÔÓÚijÖÖ²éѯ£¬ÐÔÄÜ¿ÉÄܽϵ͡£
ÁíÒ»¸öÏÞÖÆÊÇ£¬ÔªÊý¾Ý´æ´¢Ä¬ÈÏÇé¿öÏÂÊÇÒ»¸ö Derby Êý¾Ý¿â£¬²¢²»ÊÇΪÆóÒµ»òÕßÉú²ú¶ø×¼±¸¡£²¿·Ö Hadoop
Óû§×ª¶øÊ¹ÓÃÍⲿÊý¾Ý¿â×÷ΪԪÊý¾Ý´æ´¢£¬µ«ÊÇÕâЩÍⲿԪÊý¾Ý´æ´¢Ò²ÓÐÆä×ÔÉíµÄÄÑÌâºÍÅäÖÃÎÊÌâ¡£ÕâÒ²Òâζ×ÅÐèÒªÓÐÈËÔÚ
Hadoop Íⲿά»¤ºÍ¹ÜÀí RDBMS ϵͳ¡£
°²×° InfoSphere BigInsights
Õâ¸ö°ôÇòÔ˶¯Êý¾ÝʾÀýÏòÄúչʾÁËÔÚ Hive ÖÐÈçºÎ´ÓÆ½ÃæÎļþ¹¹½¨³£ÓõÄÊý¾Ý¿â¡£ËäÈ»Õâ¸öʾÀý±È½ÏС£¬µ«ËüÏÔʾÁËʹÓÃ
Hive ¹¹½¨Êý¾Ý¿âÓжàôÇáËÉ£¬Äú¿ÉÒÔʹÓøÃÊý¾ÝÔËÐÐͳ¼ÆÊý¾Ý£¬È·±£Ëü·ûºÏÔ¤ÆÚ¡£½«À´³¢ÊÔ×éÖ¯·Ç½á¹¹Êý¾Ýʱ¾ÍÎÞÐè¼ì²éÄÇЩÐÅÏ¢¡£
Íê³ÉÊý¾Ý¿â¹¹½¨Ö®ºó£¬Ö»ÒªÁ¬½Óµ½ Hive JDBC£¬¾Í¿ÉÒÔʹÓÃÈκÎÓïÑÔ¹¹½¨ Web »òÕß GUI ǰ¶Ë¡££¨ÅäÖúÍÉèÖÃÒ»¸ö
thrift ·þÎñÆ÷£¬Hive JDBC ÊÇÁíÒ»¸ö»°Ì⣩¡£ÎÒʹÓà VMware Fusion ÔÚÎÒµÄ Apple
Macbook ÉÏ´´½¨ÁËÒ»¸ö InfoSphere BigInsights ÐéÄâ»ú (VM)¡£ÕâÊÇÒ»¸ö¼òµ¥µÄ²âÊÔ£¬ÕâÑùÎÒµÄ
VM ¾ÍÓÐ 1 GB µÄ RAM ºÍ 20 GB µÄ¹Ì̬´ÅÅÌ´æ´¢¿Õ¼ä¡£²Ù×÷ϵͳÊÇ CentOS 6.4
64-bit distro µÄ Linux?¡£Äú»¹¿ÉÒÔʹÓÃijЩ¹¤¾ß£¬ÀýÈç Oracle VM VirtualBox£¬Èç¹ûÄúÊÇ
Windows? Óû§£¬ÄÇôÄú»¹¿ÉÒÔʹÓà VMware Player ´´½¨ InfoSphere BigInsights
VM¡££¨ÔÚ Fusion ÉÏÉèÖà VM¡¢VMware Player »òÕß VirtualBox ²»ÔÚ±¾ÎĵÄÌÖÂÛ·¶Î§Ö®ÄÚ¡££©
´ÓÏÂÔØ IBM InfoSphere BigInsights »ù´¡°æ¿ªÊ¼¡£ÄúÐèÒªÓÐÒ»¸ö IBM ID£¬»òÕßÄú¿ÉÒÔ×¢²áÒ»¸ö
ID£¬È»ºóÏÂÔØ InfoSphere BigInsights »ù´¡°æ¡£
ÊäÈëºÍ·ÖÎöÊý¾Ý
ÏÖÔÚ£¬Äú¿ÉÒÔÔÚÈκεط½»ñÈ¡Êý¾Ý¡£¾ø´ó¶àÊýÍøÕ¾¶¼ÌṩÁ˶ººÅ·Ö¸ôÖµ (CSV) ¸ñʽµÄÊý¾Ý£ºÌìÆø¡¢ÄÜÔ´¡¢Ô˶¯¡¢½ðÈںͲ©¿ÍÊý¾Ý¡£ÀýÈ磬ÎÒʹÓÃÀ´×Ô
Sean Lahman ÍøÕ¾µÄ½á¹¹»¯Êý¾Ý¡£Ê¹Ó÷ǽṹ»¯Êý¾Ý»á·ÑÁ¦Ò»Ð©¡£
Ê×ÏÈ ÏÂÔØ CSV Îļþ£¨²Î¼û ͼ 1£©¡£

ͼ 1. ÏÂÔØÊ¾ÀýÊý¾Ý¿â
Èç¹ûÄúÄþÔ¸ÔÚÒ»¸ö¸üÊÖ¶¯µÄ»·¾³ÖУ¬ÄÇô¿ÉÒÔ´Ó Linux? Íê³ÉËü£¬ÄúÐèÒª´´½¨Ò»¸öĿ¼£¬È»ºóÔËÐÐ
wget£º
$ Sudo mkdir /user/baseball. sudo wget http://seanlahman.com/files/database/lahman2012-csv.zip |
¸ÃÊý¾ÝʹÓÃÁË Creative Commons Attribution-ShareAlike 3.0
Unported Ðí¿É¡£
ѹËõÎļþÔÚ CSV ÎļþÖУ¬°üº¬Á˰ôÇòºÍ°ôÇòÔ˶¯Ô±µÄͳ¼ÆÊý¾Ý¡£Ê¾ÀýÖаüº¬ËĸöÖ÷±í£¬Ã¿¸ö±í¶¼Ö»ÓÐÒ»¸öÁУ¨Player_ID£©£º
Master table.csv¡ª Ô˶¯Ô±ÐÕÃû¡¢³öÉúÈÕÆÚºÍÉúƽÐÅÏ¢
Batting.csv¡ª »÷Çòͳ¼Æ
Pitching.csv¡ª ͶÇòͳ¼Æ
Fielding.csv¡ª ½ÓÇòͳ¼Æ
¸¨±í£º
AllStarFull.csv¡ª È«Ã÷ÐÇÕóÈÝ
Hall of Fame.csv¡ª ÃûÈËÌÃͶƱÊý¾Ý
Managers.csv¡ª ¹ÜÀíͳ¼Æ
Teams.csv¡ª Äê¶Èͳ¼ÆºÍÅÅÃû
BattingPost.csv¡ª Èü¼¾ºóµÄ»÷Çòͳ¼Æ
PitchingPost.csv¡ª Èü¼¾ºóµÄͶÇòͳ¼Æ
TeamFranchises.csv¡ª ¼ÓÃËÐÅÏ¢
FieldingOF.csv¡ª ³¡ÍâλÖÃÊý¾Ý
FieldingPost.csv¡ª Èü¼¾ºóµÄÏÖ³¡Êý¾Ý
ManagersHalf.csv¡ª ¾¼ÍÈ˵ķּ¾Êý¾Ý
TeamsHalf.csv¡ª ÍŶӵķּ¾Êý¾Ý
Salaries.csv¡ª ÇòԱн×ÊÊý¾Ý
SeriesPost.csv¡ª Èü¼¾ºóϵÁÐÐÅÏ¢
AwardsManagers.csv¡ª ¾¼ÍÈ˽±Ïî
AwardsPlayers.csv¡ª ÇòÔ±½±Ïî
AwardsShareManagers.csv¡ª ¾¼ÍÈ˽±ÏîͶƱ
AwardsSharePlayers.csv¡ª ÇòÔ±½±ÏîͶƱ
Appearances.csv
Schools.csv
SchoolsPlayers.csv
Éè¼ÆÊý¾Ý¿â
Éè¼ÆÊý¾Ý¿âµÄ´ó²¿·ÖÄÚÈÝÒѾÍê³É¡£Player_ID ÊÇËĸöÖ÷±í£¨Master¡¢Batting¡¢Pitching
ºÍ Fielding£©µÄÖ÷¼ü¡££¨ÎªÁ˸üºÃµØÀí½â±í¸ñ½á¹¹ºÍÒÀÀµÐÔ£¬ÇëÔĶÁ Readme2012.txt¡££©
Éè¼Æ·Ç³£¼òµ¥£ºÖ÷±íÊÇͨ¹ý Player_ID Á¬½ÓµÄ¡£Hive ²¢Ã»ÓÐÕæµÄʹÓÃÖ÷¼ü»òÕßÒýÓÃÍêÕûÐԵĸÅÄî¡£Schema
on Read Òâζ×Å Hive »áÞðÆúÄúÊäÈëµ½±í¸ñÖеÄËùÓÐÄÚÈÝ¡£Èç¹ûÎļþÊÇ»ìÂÒÎÞÐòµÄ£¬ÄÇô¿ÉÄÜÐèҪѰÇóÁ¬½ÓËüÃǵÄ×î¼Ñ·½·¨
¡£´ËÍ⣬ÔÚ½«Êý¾Ý¼ÓÔØµ½ HDFS »ò Hive ֮ǰ£¬ÐèÒª½øÐÐһЩת»¯¡£¸ù¾Ý Schema on Rea
ÔÀí£¬²»Á¼Êý¾ÝÔÚ Hive Öн«³¹µ×±ä³É²»Á¼Êý¾Ý¡£Õâ¾ÍÊÇÊý¾Ý·ÖÎö£¨ÎÞÂÛÊÇÔ´¼¶±ðµÄ»òÕß HDFS ¼¶±ðµÄ£©ÊÇÒ»¸öÖØÒª²½ÖèµÄÔÒò¡£Ã»ÓÐÊý¾Ý·ÖÎö£¬×îÖÕ»ñµÃµÄÔʼÊý¾ÝûÓÐÈË¿ÉÒÔʹÓá£ÐÒÔ˵ÄÊÇ£¬Õâ¸ö°ôÇòµÄʾÀý°üº¬Ò»Ð©Êý¾Ý£¬ÕâЩÊý¾ÝÔÚÄúÊäÈë
Hadoop ֮ǰ£¬ÒѾ±»ÇåÀíºÍ×éÖ¯µ½Ò»Æð¡£
½«Êý¾Ý¼ÓÔØµ½ HDFS »òÕß Hive
½«Êý¾Ý¼ÓÔØµ½ Hadoop ʹÓÃÁ˺ܶ಻ͬµÄÀíÂÛºÍʵ¼ù¡£ÓÐʱ£¬Äú¿ÉÒÔ½«ÔʼÎļþÖ±½ÓÊäÈëµ½ HDFS¡£Äú¿ÉÄܻᴴ½¨Ò»¸öĿ¼ºÍ×ÓĿ¼À´×éÖ¯Îļþ£¬µ«Êǽ«Îļþ´ÓÒ»¸öµØ·½¸´ÖÆ»òÒÆ¶¯µ½ÁíÒ»¸öλÖÃÊÇÒ»¸ö¼òµ¥µÄ¹ý³Ì¡£
¾ÍÕâ¸öʾÀýÀ´Ëµ£¬Ö»Ðè·¢³ö put ÃüÁȻºó´´½¨Ò»¸öÃûΪ baseball µÄĿ¼¼´¿É£º
1 2 3 Hdfs dfs -mkdir /user/hadoop/baseball hdfs dfs -put /LOCALFILE /user/hadoop/baseball |
ʹÓà Hive ¹¹½¨Êý¾Ý¿â
Ëæ×ÅÊý¾Ý·ÖÎöºÍÉè¼ÆµÄÍê³É£¬ÏÂÒ»²½¾ÍÊǹ¹½¨Êý¾Ý¿âÁË¡£
ËäÈ»ÎÒûÓнéÉÜËùÓеÄʾÀý£¬µ«ÊÇ£¬Èç¹û¸úËæÎÒ¹¹½¨Á˵ÚÒ»¸öʾÀý£¬ÄÇôÄú¾ÍÄܹ»Á˽âÈçºÎÍê³ÉʣϵIJ½Öè¡£ÎÒͨ³£»á¹¹½¨Ò»Ð©
SQL Îı¾½Å±¾£¬È»ºó½«ËüÃÇÊäÈë»òÕßÕ³Ìùµ½ Hive¡£ÆäËûÈË¿ÉÒÔʹÓà Hue »òÆäËû¹¤¾ßÀ´¹¹½¨Êý¾Ý¿âºÍ±í¸ñ¡£
ΪÁ˼ò±ãÆð¼û£¬ÎÒÃÇʹÓÃÁË Hive Shell¡£¸ß¼¶²½ÖèÊÇ£º
1.´´½¨°ôÇòÊý¾Ý¿â
2.´´½¨±í¸ñ
3.¼ÓÔØ±í¸ñ
4.ÑéÖ¤±í¸ñÊÇÕýÈ·µÄ
Äú»á¿´µ½Ò»Ð©Ñ¡ÏÀýÈ磬´´½¨Íⲿ»òÕßÄÚ²¿Êý¾Ý¿âºÍ±í¸ñ£¬µ«ÊÇÔÚÕâ¸öʾÀýÖУ¬ÐèÒª×ñÊØÄÚ²¿Ä¬ÈÏÉèÖá£Êµ¼ÊÉÏ£¬ÄÚ²¿µÄ
¾ÍÒâζ×Å Hive ´¦ÀíÁËÄÚ²¿´æ´¢µÄÊý¾Ý¿â¡£Çåµ¥ 1 ˵Ã÷ÁË Hive shell µÄÁ÷³Ì¡£
Çåµ¥ 1. ´´½¨Êý¾Ý¿â
$ Hive Create Database baseball; Create table baseball.Master ( lahmanID int, playerID int, managerID int, hofID int, birthyear INT, birthMonth INT, birthDay INT, birthCountry STRING, birthState STRING, birthCity STRING, deathYear INT, deathMonth INT, deathDay INT, deathCountry STRING, deathState STRING, deathCity STRING, nameFirst STRING, nameLast STRING, nameNote STRING, nameGive STRING, nameNick STRING, weight decimal, height decimal, bats STRING, throws STRING, debut INT, finalGame INT, college STRING, lahman40ID INT, lahman45ID INT, retroID INT, holtzID INT, hbrefID INT ) ROW FORMAT DELIMITED FIELDS TERMINATED BY ',' ; |
ÆäËûËùÓбíÒ²¶¼×ñÊØÕâ¸ö³ÌÐò¡£ÎªÁ˽«Êý¾Ý¼ÓÔØµ½ Hive ±í£¬½«»áÔٴδò¿ª Hive shell£¬È»ºóÔËÐÐÒÔÏ´úÂ룺
$hive LOAD DATA LOCAL INPATH Master.csv OVERWRITE INTO TABLE baseball.Master; |
ʹÓà Hive ¹¹½¨±ê×¼»¯Êý¾Ý¿â
Õâ¸ö°ôÇòµÄÊý¾Ý¿â»ò¶à»òÉÙÊDZê×¼»¯µÄ£ºÓÐËĸöÖ÷±íºÍ¼¸¸ö¸¨±í¡£ÔÙ´ÎÖØÉ꣬Hive ÊÇÒ»¸ö Schema on
Read£¬Òò´ËÄú±ØÐëÍê³ÉÊý¾Ý·ÖÎöºÍ ETL ½×¶ÎµÄ´ó²¿·Ö¹¤×÷£¬ÒòΪûÓд«Í³ RDBMSes ÖеÄË÷Òý»òÕßÒýÓÃÍêÕûÐÔ¡£Èç¹ûÄúÏëҪʹÓÃË÷Òý¹¦ÄÜ£¬ÄÇôÏÂÒ»²½Ó¦¸ÃʹÓÃÀàËÆ
HBase µÄ¹¤¾ß¡£Çë²é¿´ Çåµ¥ 2 ÖеĴúÂë¡£
Çåµ¥ 2. ÔËÐÐÒ»¸ö²éѯ
$ HIVE Use baseball; Select * from Master; Select PlayerID from Master; Select A.PlayerID, B.teamID, B.AB, B.R, B.H, B.2B, B.3B, B.HR, B.RBI FROM Master A JOIN BATTING B ON A.playerID = B.playerID; |
½áÊøÓï
Õâ¾ÍÊÇ Hive µÄÓÅÊÆÒÔ¼°¹¹½¨Êý¾Ý¿âµÄºÃ´¦£ºËüΪ»ìãçµÄÊÀ½ç´´½¨Á˽ṹ¡£ºÍÎÒÃÇϲ»¶ÌÖÂ۵ķǽṹ»¯»ò°ë½á¹¹»¯Êý¾ÝÒ»Ñù£¬Ëü×îÖÕ»¹ÊÇÒªÁ˽âË¿ÉÒÔ·ÖÎöÊý¾Ý£¬ËÄÜ»ùÓÚËüÔËÐб¨¸æ£¬ÒÔ¼°ÄúÈçºÎÄܹ»ÈÃËü¿ìËÙͶÈëµ½¹¤×÷ÖС£´ó¶àÊýÓû§½«
Hive ÊÓΪijÖֺںУºËûÃDz»ÔÚÒâÊý¾ÝÀ´×Ժ䦣¬Ò²²»ÔÚºõÐèÒª×öʲô²ÅÄÜÒÔÕýÈ·¸ñʽ»ñÈ¡Êý¾Ý¡£Ò²²»»áÔÚÒ⼯³É»òÕßÑéÖ¤ÕâЩÊý¾ÝÓжàôÀ§ÄÑ£¬Ö»ÒªÕâЩÊý¾ÝÊǾ«È·µÄ¡£Õâͨ³£Òâζ×ÅÄú±ØÐëÓÐ×éÖ¯ºÍ½á¹¹¡£·ñÔò£¬ÄúµÄÊý¾Ý¿â»á³ÉΪһ¸öÓÀ¾Ã´æ´¢ÎÞÏÞÖÆÊý¾ÝµÄËÀÇø£¬Ã»ÈËÄܹ»»òÕßÏëҪʹÓÃÕâЩÊý¾Ý¡£
½á¹¹¸´ÔÓµÄÊý¾Ý²Ö¿âÒѾ·ç¹â²»ÔÙ¡£ËäÈ»½üÄêÇé¿öÓÐËùºÃת£¬µ«ÊǸÅÄÊÇÒ»Ñù£ºÕâÊÇÒ»¸öÒµÎñ£¬ÒµÎñÓû§ÏëÒª½á¹û£¬¶ø²»ÊDZà³ÌÂß¼¡£Õâ¾ÍÊÇÔÚ
Hive Öй¹½¨Êý¾Ý¿â»á³ÉΪÕýÈ·¿ª¶ËµÄÔÒò¡£ |