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| Title | Views | Posted | 
|---|---|---|
| 3488 | 11-06-2018 08:19 PM | |
| 2699 | 08-31-2018 05:34 PM | |
| 1923 | 05-02-2018 02:21 PM | |
| 2756 | 04-28-2018 09:32 PM | |
| 3273 | 11-09-2017 06:02 PM | 
			
    
	
		
		
		11-07-2018
	
		
		07:07 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Correct @Matthieu Lamairesse Druid is case sensitive while Hive is not, thus, to make it work you need to make sure that all the columns are in lowercase format. 
						
					
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		11-06-2018
	
		
		08:19 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 Looked at the code and seems like the current state of the art the timestamp column is hard coded to be __time, thus that is why you are getting the exceptions since your column is called `timestamp`.   https://github.com/apache/hive/blob/a51e6aeaf816bdeea5e91ba3a0fab8a31b3a496d/druid-handler/src/java/org/apache/hadoop/hive/druid/DruidStorageHandler.java#L301  If this is the case this is a serious limitation and need to be fixed. @Nishant Bangarwa what you think? 
						
					
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		08-31-2018
	
		
		05:57 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 If you are interested on rolling up SUM and Count then you output raw data as is and "druid.query.granularity"="HOUR" (FYI not segment granularity) will do the rollup for you. If you want to compute other rollups metrics like using MIN/MAX/AVG etc then you need to do the rollup before.  If you share an example of your use cases i can help explaining more.  Thanks. 
						
					
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		08-31-2018
	
		
		05:34 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
	
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							 Please take a look at this page HDP-2.6-Hive-Druid   
 How much pre-processing is needed on the hive table creation? should i "clean" the data such that there is not further aggregation on druid or is the granularity settings will take care of aggregation on the druid side? and if so, where should those aggregations be defined? (so if i want "HOUR" granularity should i pre-process the table to group by the hours already and do all the aggregations within Hive)?    Use   "druid.query.granularity" = "HOUR"
   
 Is there any support for "HyperUnique" in this workflow? looking on doing something like "unique user ids"   sorry NO complex metrics   
 One of my challenges is that new metrics are added at a weekly/monthly basis. How will i support that if i need to load the data daily into druid? How would you handle schema evolution?    Use Insert Into for newer data and Alter table to add new columns. 
						
					
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		05-02-2018
	
		
		02:25 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 use Inset into statement   create table test_table(`timecolumn` timestamp, `userid` string, `num_l` float);
insert into test_table values ('2015-01-08 00:00:00', 'i1-start', 4);
CREATE TABLE druid_table (`__time` timestamp, `userid` string, `num_l` float)
STORED BY 'org.apache.hadoop.hive.druid.DruidStorageHandler'
TBLPROPERTIES ("druid.segment.granularity" = "DAY");
INSERT INTO TABLE druid_table
select cast(`timecolumn` as timestamp) as `__time`, `userid`, `num_l` FROM test_table;
 
						
					
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		05-02-2018
	
		
		02:21 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 It is coming from Hive conf as default. You can set it from Ambari to make it global for all sessions   hive.druid.storage.storageDirectory  https://github.com/b-slim/hive/blob/f8bc4868eced2ca83113579b626e279bbe6d5b13/common/src/java/org/apache/hadoop/hive/conf/HiveConf.java#L2626 
						
					
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		04-28-2018
	
		
		09:32 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 @ln Chari  the properties you need are   set hive.druid.metadata.db.type=postgresql;
set hive.druid.metadata.username=${DRUID_USERNAME};
set hive.druid.metadata.password=${DRUID_PASSWORD};
set hive.druid.metadata.uri=jdbc:postgresql://${METADATA_DRUID_HOST}:5432/druid;
    You were missing hive.druid.metadata.db.type  Also make sure that ${DRUID_USERNAME} are replaced with actual values  You do not need all the properties starting with druid.* 
						
					
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		04-03-2018
	
		
		11:30 PM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 In this case increasing the Ulimit of number of processes to the Druid user will fix this issue.  This Article explains more the issue and best way to fix such issue.  Exception stack.  2018-04-02T23:41:56,827 ERROR [main] io.druid.cli.CliBroker-Errorwhen starting up.Failing.java.lang.OutOfMemoryError: unable to create newnative thread at java.lang.Thread.start0(NativeMethod)~[?:1.8.0_40]at java.lang.Thread.start(Thread.java:714)~[?:1.8.0_40]at java.util.concurrent.ThreadPoolExecutor.addWorker(ThreadPoolExecutor.java:950)~[?:1.8.0_40]at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:1368)~[?:1.8.0_40]at org.jboss.netty.util.internal.DeadLockProofWorker.start(DeadLockProofWorker.java:38)~[netty-3.10.6.Final.jar:?]at org.jboss.netty.channel.socket.nio.AbstractNioSelector.openSelector(AbstractNioSelector.java:368)~[netty-3.10.6.Final.jar:?]at org.jboss.netty.channel.socket.nio.AbstractNioSelector.<init>(AbstractNioSelector.java:100)~[netty-3.10.6.Final.jar:?]at org.jboss.netty.channel.socket.nio.AbstractNioWorker.<init>(AbstractNioWorker.java:52)~[netty-3.10.6.Final.jar:?]at org.jboss.netty.channel.socket.nio.NioWorker.<init>(NioWorker.java:45)~[netty-3.10.6.Final.jar:?]at org.jboss.netty.channel.socket.nio.NioWorkerPool.newWorker(NioWorkerPool.java:44)~[netty-3.10.6.Final.jar:?]at org.jboss.netty.channel.socket.nio.NioWorkerPool.newWorker(NioWorkerPool.java:28) 
						
					
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		03-21-2018
	
		
		03:03 AM
	
	
	
	
	
	
	
	
	
	
	
	
	
	
		
	
				
		
			
					
				
		
	
		
					
							 I think your classpath is missing the HDFS module that is under extensions directory...  
						
					
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