May I know how to execute HDFS copy commands on DataProc cluster using airflow.
After the cluster is created using airflow, I have to copy few jar files from Google storage to the HDFS master node folder.
You can execute hdfs commands on dataproc cluster using something like this
gcloud dataproc jobs submit hdfs 'ls /hdfs/path/' --cluster=my-cluster --
region=europe-west1
The easiest way is [1] via
gcloud dataproc jobs submit pig --execute 'fs -ls /'
or otherwise [2] as a catch-all for other shell commands.
For a single small file
You can copy a single file from Google Cloud Storage (GCS) to HDFS using the hdfs copy command. Note that you need to run this from a node within the cluster:
hdfs dfs -cp gs://<bucket>/<object> <hdfs path>
This works because
hdfs://<master node>
is the default filesystem. You can explicitly specify the scheme and NameNode if desired:
hdfs dfs -cp gs://<bucket>/<object> hdfs://<master node>/<hdfs path>
For a large file or large directory of files
When you use hdfs dfs, data is piped through your local machine. If you have a large dataset to copy, you will likely want to do this in parallel on the cluster using DistCp:
hadoop distcp gs://<bucket>/<directory> <HDFS target directory>
Consider [3] for details.
[1] https://pig.apache.org/docs/latest/cmds.html#fs
[2] https://pig.apache.org/docs/latest/cmds.html#sh
[3] https://hadoop.apache.org/docs/current/hadoop-distcp/DistCp.html
I am not sure about your use case to do this via airflow because if its onetime setup then i think we can run commands directly on dataproc cluster. But found some links which might be of some help. As i understand we can use BashOperator and can run commands.
https://big-data-demystified.ninja/2019/11/04/how-to-ssh-to-a-remote-gcp-machine-and-run-a-command-via-airflow/
Airflow Dataproc operator to run shell scripts
Related
I had uploaded the data file to the GCS bucket of my project in Dataproc. Now I want to copy that file to HDFS. How can I do that?
For a single "small" file
You can copy a single file from Google Cloud Storage (GCS) to HDFS using the hdfs copy command. Note that you need to run this from a node within the cluster:
hdfs dfs -cp gs://<bucket>/<object> <hdfs path>
This works because hdfs://<master node> is the default filesystem. You can explicitly specify the scheme and NameNode if desired:
hdfs dfs -cp gs://<bucket>/<object> hdfs://<master node>/<hdfs path>
Note that GCS objects use the gs: scheme. Paths should appear the same as they do when you use gsutil.
For a "large" file or large directory of files
When you use hdfs dfs, data is piped through your local machine. If you have a large dataset to copy, you will likely want to do this in parallel on the cluster using DistCp:
hadoop distcp gs://<bucket>/<directory> <HDFS target directory>
Consult the DistCp documentation for details.
Consider leaving data on GCS
Finally, consider leaving your data on GCS. Because the GCS connector implements Hadoop's distributed filesystem interface, it can be used as a drop-in replacement for HDFS in most cases. Notable exceptions are when you rely on (most) atomic file/directory operations or want to use a latency-sensitive application like HBase. The Dataproc HDFS migration guide gives a good overview of data migration.
Hello I am trying to copy a file in my S3 bucket into HDFS using the cp command.
I do something like
Hadoop --config config fs -cp s3a://path hadooppath
This works well when my config is in my local.
However now I am trying to set it up as an oozie job. So when I am now unable to pass the configuration files present in config directory in my local system. Even if its in HDFS, then still it doesn't seem to work. Any suggestions ?
I tried -D command in Hadoop and passed name and value pairs, still it throws some error. It works only from my local system.
Did you Try DISTCP in oozie? Hadoop 2.7.2 will supports S3 data source. You can able to schedule it by coordinators. Just parse the credentials to coordinators either RESTAPI or in Properties files. Its easy way to copy a data periodically(Scheduled manner).
${HADOOP_HOME}/bin/hadoop distcp s3://<source>/ hdfs://<destination>/
I have a solr cloud (v 4.10) installation that sits on top of Cloudera (CDH 5.4.2) HDFS with 3 solr instances each hosting a shard of each core.
I am looking for a way to incrementally copy the solr data from our production cluster to our development cluster. There are 3 cores but I am only interested in copying one of them.
I have tried to use the Solr replication - backup and restore but that doesn't seem to load anything into the dev cluster.
http://host:8983/solr/core/replication?command=backup&location=/solr_transfer&name=core-name
http://host:8983/solr/core/replication?command=restore&location=/solr_transfer&name=core-name
I also tried to snapshot the /solr dir in the hdfs prod clusters and use hadoop disctp to copy the files but the solr indexer deletes some of the files so the distcp job fails.
hadoop distcp hftp://prod:50070/solr/* hdfs://dev:8020/solr/
Can anyone help me here?
please follow below steps to create snapshot of solr_hdfs folder and move the same on another cluster
1.Allow snapshot
sudo -u hdfs hadoop dfsadmin -allowSnapshot /user/solr/SolrCollectionName
2.Create snapshot with a specific name
sudo -u hdfs hadoop dfs -createSnapshot /user/solr/SolrCollectionName/ snapshotName
3. To list to snapshot directory
hdfs dfs -ls /user/solr/solrcollectionName/.snapshot
4. To copy, execute below command
sudo -u solr hadoop distcp hdfs://NNIP1:8020/user/solr/collectionName/.snapshot/SanpshotName hdfs://NNIP2:8020/user/solr
5. To restore snapshot
sudo -u solr hadoop fs -cp /user/solr/SanpshotName/* /user/solr/SolrcollectionName/
After a lot of trying this is the solution we worked out.
- Initialise solr in the second environment with all the collections in the same way as the primary.
- Take a snapshot of HDFS
- Use hadoop hdfs -cp to copy the data up to the checkpoint
After the first run the copy job will be quick as you are only copying the increments.
I'm trying to execute a spark program in cluster mode in Amazon Ec2 using
spark-submit --master spark://<master-ip>:7077 --deploy-mode cluster --class com.mycompany.SimpleApp ./spark.jar
And the class has a line that tries to read a file:
JavaRDD<String> logData = sc.textFile("/user/input/CHANGES.txt").cache();
I'm unable to read this txt file in cluster mode even if I'm able to read in standalone mode. In cluster mode, it's looking to read from hdfs. So I put the file in hdfs at /root/persistent-hdfs using
hadoop fs -mkdir -p /wordcount/input
hadoop fs -put /app/hadoop/tmp/input.txt /wordcount/input/input.txt
And I can see the file using hadoop fs -ls /workcount/input. But Spark is still unable to read the file. Any idea what I'm doing wrong. Thanks.
You might want to check the following points:
Is the file really in the persistent HDFS?
It seems that you just copy the input file from /app/hadoop/tmp/input.txt to /wordcount/input/input.txt, all in the node disk. I believe you misunderstand the functionality of the hadoop commands.
Instead, you should try putting the file explicitly in the persistent HDFS (root/persistent-hdfs/), and then loading it using the hdfs://... prefix.
Is the persistent HDFS server up?
Please take a look here, it seems Spark only starts the ephemeral HDFS server by default. In order to switch to the persistent HDFS server, you must do the following:
1) Stop the ephemeral HDFS server: /root/ephemeral-hdfs/bin/stop-dfs.sh
2) Start the persistent HDFS server: /root/persistent-hdfs/bin/start-dfs.sh
Please try these things, I hope they can serve you well.
How do I copy a directory in HDFS to another directory in HDFS?
I found the copyFromLocalFile functions that copy from the local FS to HDFS, but I want both of the source/destination to be in HDFS.
Thanks
Use distcp command.
The canonical use case for distcp is for transferring data between two HDFS clusters.
If the clusters are running identical versions of Hadoop, the hdfs scheme is
appropriate:
% hadoop distcp hdfs://namenode1/foo hdfs://namenode2/bar
If you want to do it through Java code, see class org.apache.hadoop.tools.DistCp and call it appropriately.
You can try FileUtil.copy
http://hadoop.apache.org/common/docs/current/api/org/apache/hadoop/fs/FileUtil.html