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How to change log level of userlogs in Hadoop 2?


How to change log level of userlogs in Hadoop 2?

By : Alihuseyn Gulmammado
Date : November 22 2020, 01:01 AM
fixed the issue. Will look into that further The actual answer was to set yarn.app.mapreduce.am.log.level to the level you need, but, crucially, it needs to be set in the Hadoop job configuration at submission time. It cannot be set on the cluster globally. The cluster global will always default to INFO, as it is hardcoded.
Using container-log4j.properties alone will not work as YARN will override the log level value on the command line. See the method addLog4jSystemProperties of org.apache.hadoop.mapreduce.v2.util.MRApps and cross reference with org.apache.hadoop.mapreduce.MRJobConfig.
code :


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How to get battery level change in android (only when there is level/percent change)?

How to get battery level change in android (only when there is level/percent change)?


By : nachsart
Date : March 29 2020, 07:55 AM
it helps some times There is no other (documented) way to get the battery level. Just ignore the broadcast when the level did not change. As you already do.
You can get the latest status immediately with the following:
code :
IntentFilter batIntentFilter = new IntentFilter(Intent.ACTION_BATTERY_CHANGED);
Intent battery = this.registerReceiver(null, batIntentFilter);
int level = battery.getIntExtra(BatteryManager.EXTRA_LEVEL, -1);
Log.d("TAG", "Current Level: " + level);
How to change the log4j level for map reduce function in hadoop

How to change the log4j level for map reduce function in hadoop


By : Peter W
Date : March 29 2020, 07:55 AM
I hope this helps . You should implement ToolRunner. In Hadoop Definitive guide there is a chapter describing it, source
How to collect Hadoop userlogs?

How to collect Hadoop userlogs?


By : Thomas
Date : March 29 2020, 07:55 AM
To fix this issue Side Note First: 2.0.0 is oldy moldy (that's the "beta" version of 2.0), you should consider upgrading to a newer stack (e.g. 2.4, 2.5 2.6).
Starting with 2.0, Hadoop implemented what's called "log aggregation" (though it's not what you would think. The logs are just stored on HDFS). There are bunch of command line tools that you can use to get the logs and analyze them without having to go through the UI. This is, in fact, much faster than the UI.
Bit-level querying in Hadoop and Hive

Bit-level querying in Hadoop and Hive


By : user7018173
Date : March 29 2020, 07:55 AM
like below fixes the issue We have a use case for bit-level querying in Hadoop. It goes something like this: , Demo
data.tsv
code :
2017-06-16 08:15:05 2DF0
2017-06-16 08:15:06 2EF0    0000
2017-06-16 08:15:07 2DF0    AAAA    BBBB    CCCC
2017-06-16 08:15:08 2EF0    1111    2222
2017-06-16 08:15:09 2DF0    
2017-06-16 08:15:10 2EF0    DDDD    EEEE
create external table mytable
(
    ts          timestamp
   ,words       string
)
row format delimited
fields terminated by '\t'
stored as textfile
tblproperties ('serialization.last.column.takes.rest'='true')
;
select  *

from    mytable
;
+----------------------------+---------------------------+
|             ts             |            words          |
+----------------------------+---------------------------+
| 2017-06-16 08:15:05.000000 | 2DF0                      |
| 2017-06-16 08:15:06.000000 | 2EF0 0000                 |
| 2017-06-16 08:15:07.000000 | 2DF0 AAAA    BBBB    CCCC |
| 2017-06-16 08:15:08.000000 | 2EF0 1111    2222         |
| 2017-06-16 08:15:09.000000 | 2DF0                      |
| 2017-06-16 08:15:10.000000 | 2EF0 DDDD    EEEE         |
+----------------------------+---------------------------+
select  ts
       ,split(words,'\\t')  as words

from    mytable
;
+----------------------------+-------------------------------+
|             ts             |             words             |
+----------------------------+-------------------------------+
| 2017-06-16 08:15:05.000000 | ["2DF0"]                      |
| 2017-06-16 08:15:06.000000 | ["2EF0","0000"]               |
| 2017-06-16 08:15:07.000000 | ["2DF0","AAAA","BBBB","CCCC"] |
| 2017-06-16 08:15:08.000000 | ["2EF0","1111","2222"]        |
| 2017-06-16 08:15:09.000000 | ["2DF0",""]                   |
| 2017-06-16 08:15:10.000000 | ["2EF0","DDDD","EEEE"]        |
+----------------------------+-------------------------------+
select  ts
       ,lpad(conv(split(words,'\\t')[0],16,2),16,'0')  as word1_bits

from    mytable
;
+----------------------------+------------------+
|             ts             |    word1_bits    |
+----------------------------+------------------+
| 2017-06-16 08:15:05.000000 | 0010110111110000 |
| 2017-06-16 08:15:06.000000 | 0010111011110000 |
| 2017-06-16 08:15:07.000000 | 0010110111110000 |
| 2017-06-16 08:15:08.000000 | 0010111011110000 |
| 2017-06-16 08:15:09.000000 | 0010110111110000 |
| 2017-06-16 08:15:10.000000 | 0010111011110000 |
+----------------------------+------------------+
select  ts

from    mytable

where   substr(lpad(conv(split(words,'\\t')[0],16,2),16,'0'),7,2) = '10'
;
+----------------------------+
|             ts             |
+----------------------------+
| 2017-06-16 08:15:06.000000 |
| 2017-06-16 08:15:08.000000 |
| 2017-06-16 08:15:10.000000 |
+----------------------------+
create external table mytable
(
    ts          timestamp
   ,word1       string
   ,word2       string
   ,word3       string
   ,word4       string
   ,word5       string
   ,word6       string
   ,word7       string
   ,word8       string
   ,word9       string
)
row format delimited
fields terminated by '\t'
stored as textfile
;
select * from mytable
;
+----------------------------+-------+--------+--------+--------+--------+--------+--------+--------+--------+
|             ts             | word1 | word2  | word3  | word4  | word5  | word6  | word7  | word8  | word9  |
+----------------------------+-------+--------+--------+--------+--------+--------+--------+--------+--------+
| 2017-06-16 08:15:05.000000 | 2DF0  | (null) | (null) | (null) | (null) | (null) | (null) | (null) | (null) |
| 2017-06-16 08:15:06.000000 | 2EF0  | 0000   | (null) | (null) | (null) | (null) | (null) | (null) | (null) |
| 2017-06-16 08:15:07.000000 | 2DF0  | AAAA   | BBBB   | CCCC   | (null) | (null) | (null) | (null) | (null) |
| 2017-06-16 08:15:08.000000 | 2EF0  | 1111   | 2222   | (null) | (null) | (null) | (null) | (null) | (null) |
| 2017-06-16 08:15:09.000000 | 2DF0  |        | (null) | (null) | (null) | (null) | (null) | (null) | (null) |
| 2017-06-16 08:15:10.000000 | 2EF0  | DDDD   | EEEE   | (null) | (null) | (null) | (null) | (null) | (null) |
+----------------------------+-------+--------+--------+--------+--------+--------+--------+--------+--------+
Hadoop MapReduce log4j - log messages to a custom file in userlogs/job_ dir?

Hadoop MapReduce log4j - log messages to a custom file in userlogs/job_ dir?


By : Brian S
Date : March 29 2020, 07:55 AM
wish of those help You can configure log4j directly in your code. For example you can call PropertyConfigurator.configure(properties); e.g. in mapper/reducer setup method.
This is example with properties stored on hdfs:
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