在 Hive 中使用横向视图时出现异常 [英] Exception while using lateral view in Hive

查看：27
本文介绍了在 Hive 中使用横向视图时出现异常的处理方法，对大家解决问题具有一定的参考价值，需要的朋友们下面随着小编来一起学习吧！

问题描述

我使用下面的代码来解析 Hive 中的 xml 数据.在我的 xml 数据中，有几个标签是重复的，所以我使用砖房罐和横向视图来解析标签并放置在 Hive 表中.但是当我执行我的代码时，我收到一个错误.请帮助，因为我无法理解我做错了什么.

I am using the below code to parse xml data in Hive. In my xml data, a few tags are repeating so I am using the brickhouse jar and lateral view to parse the tags and place in Hive tables. But when I am executing my code, I am getting an error. Please help as I am not able to understand what I am doing wrong.

代码:

add jar /home/cloudera/brickhouse-0.5.5.jar;
CREATE TEMPORARY FUNCTION numeric_range AS 'brickhouse.udf.collect.NumericRange';
CREATE TEMPORARY FUNCTION array_index AS 'brickhouse.udf.collect.ArrayIndexUDF';
add jar /home/cloudera/hivexmlserde-1.0.5.3.jar;
set hive.exec.mode.local.auto=false;
DROP TABLE IF EXISTS medinfo2;
create table medinfo2 as
select array_index(statusCode,n) AS statusCode,
    array_index(startTime,n) AS startTime,
    array_index(endTime,n) AS endTime,
    array_index(strengthValue,n) AS strengthValue,
    array_index(strengthUnits,n) AS strengthUnits
from medications_info7 lateral view numeric_range(size( statusCode )) n1 as n;

错误:

引起:java.lang.IndexOutOfBoundsException:索引:7，大小:7在 java.util.ArrayList.rangeCheck(ArrayList.java:635)在 java.util.ArrayList.get(ArrayList.java:411)在 com.ibm.spss.hive.serde2.xml.objectinspector.XmlListObjectInspector.getListElement(XmlListObjectInspector.java:79)在brickhouse.udf.collect.ArrayIndexUDF.evaluate(ArrayIndexUDF.java:59)在 org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator._evaluate(ExprNodeGenericFuncEvaluator.java:186)在 org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:77)在 org.apache.hadoop.hive.ql.exec.ExprNodeEvaluatorHead._evaluate(ExprNodeEvaluatorHead.java:44)在 org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:77)在 org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:65)在 org.apache.hadoop.hive.ql.exec.SelectOperator.processOp(SelectOperator.java:77)……还有 25 个

Caused by: java.lang.IndexOutOfBoundsException: Index: 7, Size: 7 at java.util.ArrayList.rangeCheck(ArrayList.java:635) at java.util.ArrayList.get(ArrayList.java:411) at com.ibm.spss.hive.serde2.xml.objectinspector.XmlListObjectInspector.getListElement(XmlListObjectInspector.java:79) at brickhouse.udf.collect.ArrayIndexUDF.evaluate(ArrayIndexUDF.java:59) at org.apache.hadoop.hive.ql.exec.ExprNodeGenericFuncEvaluator._evaluate(ExprNodeGenericFuncEvaluator.java:186) at org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:77) at org.apache.hadoop.hive.ql.exec.ExprNodeEvaluatorHead._evaluate(ExprNodeEvaluatorHead.java:44) at org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:77) at org.apache.hadoop.hive.ql.exec.ExprNodeEvaluator.evaluate(ExprNodeEvaluator.java:65) at org.apache.hadoop.hive.ql.exec.SelectOperator.processOp(SelectOperator.java:77) ... 25 more

失败:执行错误，从 org.apache.hadoop.hive.ql.exec.mr.MapRedTask 返回代码 2MapReduce 作业启动:Stage-Stage-1:映射:1 HDFS 读取:0 HDFS 写入:0 失败MapReduce CPU 总耗时:0 毫秒

FAILED: Execution Error, return code 2 from org.apache.hadoop.hive.ql.exec.mr.MapRedTask MapReduce Jobs Launched: Stage-Stage-1: Map: 1 HDFS Read: 0 HDFS Write: 0 FAIL Total MapReduce CPU Time Spent: 0 msec

示例:

<document>
 <code>10160-0</code>
 <entryInfo> 
    <statusCode>completed</statusCode>
    <startTime>20110729</startTime>
    <endTime>20110822</endTime>
    <strengthValue>24</strengthValue>
    <strengthUnits>h</strengthUnits>
 </entryInfo> 
 <entryInfo>
    <statusCode>completed</statusCode>
    <startTime>20120130</startTime>
    <endTime>20120326</endTime>
    <strengthValue>12</strengthValue>
    <strengthUnits>h</strengthUnits>
 </entryInfo>
 <entryInfo>
    <statusCode>completed</statusCode>
    <startTime>20100412</startTime>
    <endTime>20110822</endTime>
    <strengthValue>8</strengthValue>
    <strengthUnits>d</strengthUnits>
 </entryInfo>  
</document>

我的实际样本很大，包含很多重复的这些标签.

My actual sample is huge in size and contains a lot of these tags which are repeated.

推荐答案

我不知道你的数据在 Hive 中是什么样子，因为你没有提供这些信息，所以这里是我如何将你的 XML 加载到 Hive 中.

I don't know what your data looks like in Hive because you didn't provide that information so here is how I loaded your XML into Hive.

加载器:

ADD JAR /path/to/jar/hivexmlserde-1.0.5.3.jar;

DROP TABLE IF EXISTS db.tbl;
CREATE TABLE IF NOT EXISTS db.tbl (
  code STRING,
  entryInfo ARRAY<MAP<STRING,STRING>>
)
ROW FORMAT SERDE 'com.ibm.spss.hive.serde2.xml.XmlSerde'
WITH SERDEPROPERTIES (
  "column.xpath.code"="/document/code/text()",
  "column.xpath.entryInfo"="/document/entryInfo/*"
)
STORED AS
INPUTFORMAT 'com.ibm.spss.hive.serde2.xml.XmlInputFormat'
OUTPUTFORMAT 'org.apache.hadoop.hive.ql.io.IgnoreKeyTextOutputFormat'
TBLPROPERTIES (
  "xmlinput.start"="<document>",
  "xmlinput.end"="</document>"
);

LOAD DATA LOCAL INPATH 'someFile.xml' INTO TABLE db.tbl;

在 Hive-XML-SerDe在 3 - Arrays 部分下的文档，你可以看到他们使用数组结构来处理重复的标签，在 4 - Maps 中，你可以看到他们使用 map 来处理条目在子标签下.因此，entryInfo 的类型为 ARRAY>.

In the Hive-XML-SerDe documentation under section 3 - Arrays, you can see that they use an array structure to handle repeated tags and in 4 - Maps, you can see that they use maps to handle entries under a sub-tag. So, entryInfo will be of type ARRAY<MAP<STRING,STRING>>.

然后你可以分解这个数组，像 key/vals 一样收集，然后重新组合.

You can then explode this array, collect like key/vals, and re-combine.

查询:

ADD JAR /path/to/jar/hivexmlserde-1.0.5.3.jar;
ADD JAR /path/to/jars/brickhouse-0.7.1.jars;

CREATE TEMPORARY FUNCTION COLLECT AS 'brickhouse.udf.collect.CollectUDAF';

SELECT code
  , m_map['statusCode']    AS status_code
  , m_map['startTime']     AS start_time
  , m_map['endTime']       AS end_time
  , m_map['strengthValue'] AS strength_value
  , m_map['strengthUnits'] AS strength_units
FROM (
  SELECT code
    , COLLECT(m_keys, m_vals) AS m_map
  FROM (
    SELECT code
      , idx
      , MAP_KEYS(entry_info_map)[0]   AS m_keys
      , MAP_VALUES(entry_info_map)[0] AS m_vals
    FROM (
      SELECT code
        , entry_info_map
        , CASE
           WHEN FLOOR(tmp / 5) = 0 THEN 0
           WHEN FLOOR(tmp / 5) = 1 THEN 1
           WHEN FLOOR(tmp / 5) = 2 THEN 2
           ELSE -1
         END AS idx
      FROM db.tbl
      LATERAL VIEW POSEXPLODE(entryInfo) exptbl AS tmp, entry_info_map ) x ) y
  GROUP BY code, idx ) z

输出:

code    status_code     start_time      end_time    strength_value  strength_units
10160-0 completed       20110729        20110822    24              h
10160-0 completed       20120130        20120326    12              h
10160-0 completed       20100412        20110822    8               d

此外，您基本上已经问过这个问题 4 次了(一个，两个，三个、四个).这不是一个好主意.只需询问一次，编辑以添加更多信息，并耐心等待.

Also, you've basically asked this question 4 times (one, two, three, four). This is not a good idea. Just ask once, edit to add more information, and be patient.

这篇关于在 Hive 中使用横向视图时出现异常的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！

查看全文
相关文章
其他开发最新文章
热门教程
热门工具
登录 关闭
扫码关注1秒登录
发送“验证码”获取 | 15天全站免登陆