I am trying to working with Pentaho, in order to build some big data solutions. But the Hadoop HBase components aren't appering in the dashboard. I don't understand why HBase doesn't appear, since HBase is up an running on my machine... I've been seeking for a solutions, but without success...
Please check this property value 'hbase.client.scanner.timeout.period' set to 10 mins in hbase-default.xml to get rid of hbase exceptions.
Check that you have added zookeeper host in the hbase output host in pentaho data integration tool.
Have you read this wiki in order to load hbase data into pentaho.
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I am new to Hadoop ecosystem and self learning it through online articles.
I am working on very basic project so that I can get hands-on on what I have learnt.
My use-case is extremely: Idea is I want to present location of user who login to portal to app admin.So, I have a server which is continuously generating logs, logs have user id, IP address, time-stamp. All fields are comma separated.
My idea to do this is to have a flume agent to streaming live logs data and write to HDFS. Have HIVE process in place which will read incremental data from HDFS and write to HIVE table. Use scoop to continuously copy data from HIVE to RDMBS SQL table and use that SQL table to play with.
So far I have successfully configured flume agent which read logs from a given location and write to hdfs location. But after this I am confused as how should I move data from HDFS to HIVE table. One idea that's coming to my mind is to have a MapRed program that will read files in HDFS and write to HIVE tables programatically in Java. But I also want to delete files which are already processed and make sure that no duplicate records are read by MapRed. I searched online and found command that can be used to copy file data to HIVE but that's sort of a manual once activity. In my usecase I want to push data as soon as it's available in HDFS.
Please guide me how to achieve this task. Links will be helpful.
I am working on Version: Cloudera Express 5.13.0
Update 1:
I just created an external HIVE table pointing to HDFS location where flume is dumping logs. I noticed that as soon as table is created, I can query HIVE table and fetch data. This is awesome. But what will happen if I stop flume agent for time being, let app server to write logs, now if I start flume again then will flume only read new logs and ignore logs which are already processed? Similarly, will hive read new logs which are not processed and ignore the ones which it has already processed?
how should I move data from HDFS to HIVE table
This isn't how Hive works. Hive is a metadata layer over existing HDFS storage. In Hive, you would define an EXTERNAL TABLE, over wherever Flume writes your data to.
As data arrives, Hive "automatically knows" that there is new data to be queried (since it reads all files under the given path)
what will happen if I stop flume agent for time being, let app server to write logs, now if I start flume again then will flume only read new logs and ignore logs which are already processed
Depends how you've setup Flume. AFAIK, it will checkpoint all processed files, and only pick up new ones.
will hive read new logs which are not processed and ignore the ones which it has already processed?
Hive has no concept of unprocessed records. All files in the table location will always be read, limited by your query conditions, upon each new query.
Bonus: Remove Flume and Scoop. Make your app produce records into Kafka. Have Kafka Connect (or NiFi) write to both HDFS and your RDBMS from a single location (Kafka topic). If you actually need to read log files, Filebeat or Fluentd take less resources than Flume (or Logstash)
Bonus 2: Remove HDFS & RDBMS and instead use a more real-time ingestion pipeline like Druid or Elasticsearch for analytics.
Bonus 3: Presto / SparkSQL / Flink-SQL are faster than Hive (note: the Hive metastore is actually useful, so keep the RDBMS around for that)
I am trying to create an ORC table in Hive by importing from a text file in HDFS. I have tried multiple different ways, searched online for help, and regardless the insert job won't start.
I can get the text file to HDFS, I can read the text file to Hive, but I cannot convert from that to ORC.
I tried many different variations, including this one that can be used as a reference to this question:
http://docs.hortonworks.com/HDPDocuments/HDP2/HDP-2.3.0/bk_dataintegration/content/moving_data_from_hdfs_to_hive_external_table_method.html
I have a single-node HDP cluster (being used for development) - version:
HDP-2.3.2.0
(2.3.2.0-2950)
And here are the relevant service versions:
Service Version Status Description
HDFS 2.7.1.2.3 Installed Apache Hadoop Distributed File System
MapReduce2 2.7.1.2.3 Installed Apache Hadoop NextGen MapReduce (YARN)
YARN 2.7.1.2.3 Installed Apache Hadoop NextGen MapReduce (YARN)
Tez 0.7.0.2.3 Installed Tez is the next generation Hadoop Query Processing framework written on top of YARN.
Hive 1.2.1.2.3 Installed Data warehouse system for ad-hoc queries & analysis of large datasets and table & storage management service
What happens when I run a SQL like this (again, I've tried many variations including directly from online tutorials):
INSERT OVERWRITE TABLE mycars SELECT * FROM cars;
My job stays like this:
Total number of applications (application-types: [] and states:
[SUBMITTED, ACCEPTED, RUNNING]):1
Application-Id Application-Name Application-Type User Queue State Final-State Progress Tracking-URL
application_1455989658079_0002 HIVE-3f41161c-b806-4e7d-974e-c18e028d683f TEZ hive root.hive ACCEPTED UNDEFINED 0% N/A
And it just hangs there. (Literally, I've tried a 20 row sample table and let it run for hours before killing it).
I am by no means an Hadoop expert (yet) and am sure it's probably a config issue, but I have been unable to figure it out.
All other Hive operations I've tried, such as creating dropping tables, loading a file to a text table, selects, all work fine. It's just when I create an ORC table that it does this. And I need an ORC table for my requirement.
Any advice would be helpful.
Most of the time it has to do with increasing your Yarn Scheduling capacity, but if your resources are already capped you can also reduce the amount of memory requested by individual TEZ tasks, through adjusting the following property in TEZ configuration :
task.resource.memory.mb
In order to increase the Cluster's capacity you can do it in the configuration settings of YARN or directly through Ambari or Cloudera Manager
In order to monitor what is happening behind the hoods you can run Yarn Resource Manager UI and check the diagnostics tab of the specific Application there are useful explicit messages about resource allocation especially when the job is accepted and keeps pending.
I have set up a single node hadoop cluster on ubuntu.I have installed hadoop 2.6 version on in my machine.
Problem:
Everytime i create HIVE tables and load data into it , i can see the data by querying on it but once i shut-down my hadoop , tables gets wiped out. Is there any way i can retain them or is there any setting i am missing?
I tried some online solution provided , but nothing worked , kindly help me out with this.
Blockquote
Thanks
B
The hive table data is on the hadoop hdfs, hive just add a meta data and provide users sql like commands to prevent them from writing basic MR jobs.So if you shutdown the hadoop cluster,Hive cant find the data in the table.
But if you are saying when you restart the hadoop cluster, the data is lost.That's another problem.
seems you are using default derby as metastore.configure the hive metastore.i am pointing the link.please fallow it.
Hive is not showing tables
I found a post that discusses about connecting Tableau to Elastic Search via Hive SQL. I was wondering if there is a way to connect to Elastic Search via Spark SQL as I am not much familiar with hive.
Thanks.
#busybug91,
The right driver is here please try with this one. Could be solve your issue.
#NicholasY It got it resolved after a couple of trials. Two steps that I took:-
I wasn't using the right driver for connection. I was using datastax enterprise driver. However, they have a driver for spark sql as well. I used windows 64bit version of driver. Using MapR Hadoop Hive and Hortonworks Hadoop Hive drivers didn't work as I've Apache hive.
When I used right driver (from DataStax) I realized that my hive metastore and spark-thrift-server running on same port. I changed spark-thrift-server's port to 10001 and a successful connection was established.
A new problem: I've created external table in hive. I am able to query the data as well. I start hive-metastore as a service. However, as mentioned on this link I am not able to see my tables in hive in Spark SQL. My connection of Tableau with Spark Sql is of no use unless I see tables from hive metastore!! When I do show tables; in spark sql (via spark-sql shell and hive metastore running as a service as same time), it runs a job which gives a completion time also but now table names. I monitored it via localhost:4040 I see that input and output size are 0.0. I believe I am not able to get tables from hive in spark sql that is why I don't see any table after connection is established from Tableau to spark sql.
EDIT
I changed metastore from derby to mysql for both hive and spark sql.
I'm trying to do that, so maybe i can help you to warn up something.
First, compile a Spark SQL version with Hive and thrift Server (ver 0.13):
export MAVEN_OPTS="-Xmx2g -XX:MaxPermSize=512M -XX:ReservedCodeCacheSize=512m"
mvn -Pyarn -Phadoop-2.4 -Dhadoop.version=2.4.0 -Phive -Phive-thriftserver -DskipTests clean package
You need to have a hive-site.xml properly configurered to work with Hive and to copy it to spark/conf folder.
Then, you have to set the $CLASSPATH with the elasticsearch-hadoop jar path.
Be careful ! Spark SQL 1.2.0 is not working with elasticsearch-hadoop-2.0.x. You have to use a elasticsearch-hadoop-2.1.0-Beta4 or BUILD-SNAPSHOT available here.
To finish you have to run thriftserver with something like that:
./start-thriftserver.sh --master spark://master:7077 --driver-class-path $CLASSPATH --jars /root/spark-sql/spark-1.2.0/lib/elasticsearch-hadoop-2.1.0.Beta4.jar --hiveconf hive.server2.thrift.bind.host 0.0.0.0 --hiveconf hive.server2.thrift.port 10000
It works for me but only on small docType ( 5000 rows ) , the data-colocation seems not working. I looking for a solution to move elasticsearch-hadoop.jar on each Spark workers as ryrobes did for Hadoop.
If you find a way to locate access to elasticsearch, let me know ;)
HTH,
I'm running hbase(0.94.13) on a single node for my academic project. After loading data into hbase tables, I'm trying to run pig(0.11.1) scripts on the data using HBaseStorage. However this throws an error saying
IllegalArgumentException: Not a host:port pair: �\00\00\00
here is the load command I'm using in Pig
books = LOAD 'hbase://booksdb' USING
org.apache.pig.backend.hadoop.hbase.HBaseStorage('details:title','-loadKey
true') AS (ID:chararray,title:chararray);
I thought this might be a problem of hbase being a different version in pig than what my machine has. But can't seem to make it work without downgrading my hbase. Any help?
It seems you are trying to submit a pig job remotely
if so you'd need to add a few settings in the pig.properties file (or set setting_name='values' in your script)
hbase.zookeeper.quorum=<node>
hadoop.job.ugi=username,groupname
fs.default.name=hdfs://<node>:port
mapred.job.tracker=hdfs://<node>:port