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python - 在 hive 或 pyspark 中透视日志

coder 2024-01-08 原文

我有很多这种格式的文件日志:

[Windows user      ] Pâmela
[Host name         ] DV6000
[Local time        ] 14:25:07
[System time       ] 17:25:07
[ASCWebBrowser info] 1.1.1
[Last Write Time   ] 07/19/2016  14:01
[HD Info           ] Volume name: , Serial: 1713925408, File System: NTFS, Max Component Length: 255
[Network Info
 [Index            ] 48
 [Type             ] 1
 [Description      ] TAP-Win32 Adapter OAS #6
 [Name             ] {343D77F2-B3CE-414B-AE01-E248D3FC85F6}
 [Ip address       ] 169.254.92.162
 [MAC Address      ] 00-FF-34-3D-77-F2
 [Gateway          ] 0.0.0.0
 [Mask             ] 255.255.0.0

 [Index            ] 38
 [Type             ] 1
 [Description      ] TAP-Windows Adapter V9 #6
 [Name             ] {C81FC3F7-19F9-44DD-9470-4982F48A141D}
 [Ip address       ] 169.254.96.118
 [MAC Address      ] 00-FF-C8-1F-C3-F7
 [Gateway          ] 0.0.0.0
 [Mask             ] 255.255.0.0

 [Index            ] 36
 [Type             ] 1
 [Description      ] TAP-Win32 Adapter OAS #5
 [Name             ] {72115AC7-4EE2-4CB3-A8D2-
]

我需要将每一行转换成一列。如您所见,有 1 个或多个网络信息。那将是一张子表,其余的都是父表。我已经通过 Hive 阅读了这个日志,但我现在仍然停留在如何旋转/转置它上。

到目前为止,我已经尝试了以下方法:

  1. Spark DataFrame 枢轴。没办法,因为需要聚合。
  2. Pandas DataFrame 枢轴。它提示索引重复。相同的信息可以出现在不同的日志中,因此唯一唯一的是文件名。
  3. Hive 中的 SQL CASE 方法。它不生成线性信息。有许多 NULL。
  4. 加入。尝试使用文件名作为连接列进行自连接,但它会生成笛卡尔结果。 RowNumber 是由 dense_rank) 在 fname 上生成的列。问题是对于每个 IP,它都连接到每个描述,而不仅仅是相同的描述。因此,对于 2 个 IP,它为每个掩码创建 4 行,8 行,依此类推。

    select coalesce(hn.value, "No_Name") as hostname, d.value as decription, 
        g.value as gateway,i.value as "index", p.value as IP, mc.value as MAC,
        m.value as Mask, n.value as "Name", t.value as "Type" 
    from net_asclogs_p hn left join net_asclogs_p d on hn.fname=d.fname and d.rownumber= 1 
        left join net_asclogs_p g on hn.fname=g.fname and g.rownumber=2 
        left join net_asclogs_p i on hn.fname=i.fname and i.rownumber=4 
        left join net_asclogs_p p on hn.fname=p.fname and p.rownumber=5 
        left join net_asclogs_p mc on hn.fname=mc.fname and mc.rownumber=6 
        left join net_asclogs_p m on hn.fname=m.fname and m.rownumber=7 
        left join net_asclogs_p n on hn.fname=n.fname and n.rownumber=8 
        left join net_asclogs_p t on hn.fname=t.fname and t.rownumber=9 
    where hn.rownumber=3;
    
  5. 尝试了 Brickhouse 的 Collect,但它只带来了最后一条记录,而不是全部。

  6. 尝试了 RegexSerde,但我确定我在这里没有得到任何东西,因为所有字段都是空的:

    CREATE EXTERNAL TABLE IF NOT EXISTS asclogs1 (host string, index string) 
        ROW FORMAT SERDE 'org.apache.hadoop.hive.serde2.RegexSerDe' WITH SERDEPROPERTIES 
            ( "input.regex" = "Host name\\s{2,}\\]\\s(\\w+)|Index\\s{2,}\\]\\s(\\w+).*",
            "output.format.string" = "%1$s %2$s" ) 
        STORED AS TEXTFILE LOCATION 'hdfs:///asclogs/'
    

好吧,我没主意了。最后的办法是用 Java 编写自定义类。有其他选择吗?

最佳答案

create external table log (key string,val string)
row format serde 'org.apache.hadoop.hive.serde2.RegexSerDe'
with serdeproperties ("input.regex" = "\\s*\\[(.*?)\\s*(?:\\]|$)\\s*(.*)")
;

select * from log
;

+--------------------+---------------------------------------------------------------------------------+
|        key         |                                       val                                       |
+--------------------+---------------------------------------------------------------------------------+
| Windows user       | Pâmela                                                                          |
| Host name          | DV6000                                                                          |
| Local time         | 14:25:07                                                                        |
| System time        | 17:25:07                                                                        |
| ASCWebBrowser info | 1.1.1                                                                           |
| Last Write Time    | 07/19/2016  14:01                                                               |
| HD Info            | Volume name: , Serial: 1713925408, File System: NTFS, Max Component Length: 255 |
| Network Info       |                                                                                 |
| Index              | 48                                                                              |
| Type               | 1                                                                               |
| Description        | TAP-Win32 Adapter OAS #6                                                        |
| Name               | {343D77F2-B3CE-414B-AE01-E248D3FC85F6}                                          |
| Ip address         | 169.254.92.162                                                                  |
| MAC Address        | 00-FF-34-3D-77-F2                                                               |
| Gateway            | 0.0.0.0                                                                         |
| Mask               | 255.255.0.0                                                                     |
| (null)             | (null)                                                                          |
| Index              | 38                                                                              |
| Type               | 1                                                                               |
| Description        | TAP-Windows Adapter V9 #6                                                       |
| Name               | {C81FC3F7-19F9-44DD-9470-4982F48A141D}                                          |
| Ip address         | 169.254.96.118                                                                  |
| MAC Address        | 00-FF-C8-1F-C3-F7                                                               |
| Gateway            | 0.0.0.0                                                                         |
| Mask               | 255.255.0.0                                                                     |
| (null)             | (null)                                                                          |
| Index              | 36                                                                              |
| Type               | 1                                                                               |
| Description        | TAP-Win32 Adapter OAS #5                                                        |
| Name               | {72115AC7-4EE2-4CB3-A8D2-                                                       |
| (null)             | (null)                                                                          |
+--------------------+---------------------------------------------------------------------------------+

select      max (Windows_user)          as Windows_user 
           ,max (Host_name)             as Host_name
           ,max (Local_time)            as Local_time
           ,max (System_time)           as System_time
           ,max (ASCWebBrowser_info)    as ASCWebBrowser_info
           ,max (Last_Write_Time)       as Last_Write_Time
           ,max (HD_Info)               as HD_Info

           ,collect_list 
            (
                case when nwi_seq > 0 then
                    named_struct
                    (
                        'Index'         ,Index
                       ,'Type'          ,Type
                       ,'Description'   ,Description
                       ,'Name'          ,Name
                       ,'Ip_address'    ,Ip_address
                       ,'MAC_Address'   ,MAC_Address
                       ,'Gateway'       ,Gateway
                       ,'Mask'          ,Mask                   
                    )
                end
            )       as Network_Info

from       (select      ifn
                       ,log_seq
                       ,nwi_seq

                       ,max (case when nwi_seq = 0 and key = 'Windows user'         then val end)   as Windows_user
                       ,max (case when nwi_seq = 0 and key = 'Host name'            then val end)   as Host_name
                       ,max (case when nwi_seq = 0 and key = 'Local time'           then val end)   as Local_time
                       ,max (case when nwi_seq = 0 and key = 'System time'          then val end)   as System_time
                       ,max (case when nwi_seq = 0 and key = 'ASCWebBrowser info'   then val end)   as ASCWebBrowser_info
                       ,max (case when nwi_seq = 0 and key = 'Last Write Time'      then val end)   as Last_Write_Time
                       ,max (case when nwi_seq = 0 and key = 'HD Info'              then val end)   as HD_Info

                       ,max (case when nwi_seq > 0 and key = 'Index'                then val end)   as Index      
                       ,max (case when nwi_seq > 0 and key = 'Type'                 then val end)   as Type       
                       ,max (case when nwi_seq > 0 and key = 'Description'          then val end)   as Description
                       ,max (case when nwi_seq > 0 and key = 'Name'                 then val end)   as Name       
                       ,max (case when nwi_seq > 0 and key = 'Ip address '          then val end)   as Ip_address 
                       ,max (case when nwi_seq > 0 and key = 'MAC Address'          then val end)   as MAC_Address
                       ,max (case when nwi_seq > 0 and key = 'Gateway'              then val end)   as Gateway    
                       ,max (case when nwi_seq > 0 and key = 'Mask'                 then val end)   as Mask                         

            from       (select      key
                                   ,val
                                   ,ifn
                                   ,log_seq

                                   ,count(case when key = 'Index' then 1 end) over
                                    (
                                        partition by    ifn,log_seq
                                        order by        boif
                                    ) as nwi_seq

                        from       (select  key
                                           ,val
                                           ,input__file__name               as ifn
                                           ,block__offset__inside__file     as boif

                                           ,count(case when key = 'Windows user' then 1 end) over 
                                            (
                                                partition by    input__file__name
                                                order by        block__offset__inside__file
                                            ) as log_seq


                                    from    log
                                    ) l
                        ) l

            group by    ifn
                       ,log_seq
                       ,nwi_seq
            ) l

group by    ifn
           ,log_seq
;

+--------------+-----------+------------+-------------+--------------------+-------------------+---------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| windows_user | host_name | local_time | system_time | ascwebbrowser_info |  last_write_time  |                                     hd_info                                     |                                                                                                                                                                                                                                                                                               network_info                                                                                                                                                                                                                                                                                               |
+--------------+-----------+------------+-------------+--------------------+-------------------+---------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Pâmela       | DV6000    | 14:25:07   | 17:25:07    | 1.1.1              | 07/19/2016  14:01 | Volume name: , Serial: 1713925408, File System: NTFS, Max Component Length: 255 | [{"index":"48","type":"1","description":"TAP-Win32 Adapter OAS #6","name":"{343D77F2-B3CE-414B-AE01-E248D3FC85F6}","ip_address":null,"mac_address":"00-FF-34-3D-77-F2","gateway":"0.0.0.0","mask":"255.255.0.0"},{"index":"38","type":"1","description":"TAP-Windows Adapter V9 #6","name":"{C81FC3F7-19F9-44DD-9470-4982F48A141D}","ip_address":null,"mac_address":"00-FF-C8-1F-C3-F7","gateway":"0.0.0.0","mask":"255.255.0.0"},{"index":"36","type":"1","description":"TAP-Win32 Adapter OAS #5","name":"{72115AC7-4EE2-4CB3-A8D2-","ip_address":null,"mac_address":null,"gateway":null,"mask":null}] |
+--------------+-----------+------------+-------------+--------------------+-------------------+---------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+

关于python - 在 hive 或 pyspark 中透视日志,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/44558044/

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