source: gs3-extensions/maori-lang-detection/MoreReading/Vagrant-Spark-Hadoop.txt@ 33441

To run firefox/anything graphical inside the VM run by vagrant, have to ssh -Y onto both analytics and then to the vagrant VM from analytics:
1. ssh analytics -Y
2. [anupama@analytics vagrant-hadoop-hive-spark]$ vagrant ssh -- -Y
or
vagrant ssh -- -Y node1
(the -- flag tells the vagrant command that the subsequent -Y flag should be passed to the ssh cmd that vagrant runs)

Only once ssh-ed with vagrant into the VM whose hostname is "node1", do you have access to node1's assigned IP: 10.211.55.101
- Connecting machines, like analytics, must access node1 or use port forwarding to view the VM's servers on localhost. For example, on analytics, can view Yarn pages at http://localhost:8088/
- If firefox is launched inside the VM (so inside node1), then can access pages off their respective ports at any of localhost|10.211.55.101|node1.

-------------------------


WET example from https://github.com/commoncrawl/cc-warc-examples

vagrant@node1:~/cc-warc-examples$ hdfs dfs -mkdir /user/vagrant/data
vagrant@node1:~/cc-warc-examples$ hdfs dfs -put data/CC-MAIN-20190715175205-20190715200159-00000.warc.wet.gz hdfs:///user/vagrant/data/.
vagrant@node1:~/cc-warc-examples$ hdfs dfs -ls data
Found 1 items
-rw-r--r--   1 vagrant supergroup  154823265 2019-08-19 08:23 data/CC-MAIN-20190715175205-20190715200159-00000.warc.wet.gz
vagrant@node1:~/cc-warc-examples$ hadoop jar target/cc-warc-examples-0.3-SNAPSHOT-jar-with-dependencies.jar org.commoncrawl.examples.mapreduce.WETWordCount

<ONCE FINISHED:>

vagrant@node1:~/cc-warc-examples$ hdfs dfs -cat /tmp/cc/part*



INFO ON HADOOP/HDFS:
https://www.bluedata.com/blog/2016/08/hadoop-hdfs-upgrades-painful/

SPARK:
configure option example: https://stackoverflow.com/questions/46152526/how-should-i-configure-spark-to-correctly-prune-hive-metastore-partitions



LIKE '%isl%'

cd cc-index-table
APPJAR=target/cc-spark-0.2-SNAPSHOT-jar-with-dependencies.jar
> $SPARK_HOME/bin/spark-submit \
#    $SPARK_ON_YARN \
   --conf spark.hadoop.parquet.enable.dictionary=true \
   --conf spark.hadoop.parquet.enable.summary-metadata=false \
   --conf spark.sql.hive.metastorePartitionPruning=true \
   --conf spark.sql.parquet.filterPushdown=true \
   --conf spark.sql.parquet.mergeSchema=true \
   --class org.commoncrawl.spark.examples.CCIndexWarcExport $APPJAR \
   --query "SELECT url, warc_filename, warc_record_offset, warc_record_length
            FROM ccindex
            WHERE crawl = 'CC-MAIN-2019-30' AND subset = 'warc' AND content_languages LIKE '%mri%'" \
   --numOutputPartitions 12 \
   --numRecordsPerWarcFile 20000 \
   --warcPrefix ICELANDIC-CC-2018-43 \
   s3://commoncrawl/cc-index/table/cc-main/warc/ \
   .../my_output_path/


=========================================================
Configuring spark to work on Amazon AWS s3a dataset:
=========================================================
https://stackoverflow.com/questions/30385981/how-to-access-s3a-files-from-apache-spark
http://deploymentzone.com/2015/12/20/s3a-on-spark-on-aws-ec2/
https://answers.dataiku.com/1734/common-crawl-s3
https://stackoverflow.com/questions/2354525/what-should-be-hadoop-tmp-dir
https://stackoverflow.com/questions/40169610/where-exactly-should-hadoop-tmp-dir-be-set-core-site-xml-or-hdfs-site-xml

https://stackoverflow.com/questions/43759896/spark-truncated-the-string-representation-of-a-plan-since-it-was-too-large-w

===========================================
IAM Role (or user) and commoncrawl profile
===========================================

"iam" role or user for commoncrawl(er) profile


aws management console:
[email protected]
lab pwd, capital R and ! (maybe g)

commoncrawl profile created while creating the user/role, by following the instructions at: https://answers.dataiku.com/1734/common-crawl-s3

<!--
    <property>
      <name>fs.s3a.awsAccessKeyId</name>
      <value>XXX</value>
    </property>
    <property>
      <name>fs.s3a.awsSecretAccessKey</name>
      <value>XXX</value>
    </property>
-->


But instead of putting the access and secret keys in hadoop's core-site.xml as above (with sudo emacs /usr/local/hadoop-2.7.6/etc/hadoop/core-site.xml)

you'll want to put the Amazon AWS access key and secret key in the spark properties file:

       sudo emacs /usr/local/spark-2.3.0-bin-hadoop2.7/conf/spark-defaults.conf


The spark properties should contain:

spark.hadoop.fs.s3a.impl=org.apache.hadoop.fs.s3a.S3AFileSystem  
spark.hadoop.fs.s3a.access.key=ACCESSKEY  
spark.hadoop.fs.s3a.secret.key=SECRETKEY  


-------------

APPJAR=target/cc-spark-0.2-SNAPSHOT-jar-with-dependencies.jar
$SPARK_HOME/bin/spark-submit \
    --conf spark.hadoop.parquet.enable.dictionary=true \
    --conf spark.hadoop.parquet.enable.summary-metadata=false \
    --conf spark.sql.hive.metastorePartitionPruning=true \
    --conf spark.sql.parquet.filterPushdown=true \
    --conf spark.sql.parquet.mergeSchema=true \
    --class org.commoncrawl.spark.examples.CCIndexExport $APPJAR \
        --query "SELECT url, warc_filename, warc_record_offset, warc_record_length   
            FROM ccindex                                                        
            WHERE crawl = 'CC-MAIN-2019-30' AND subset = 'warc' AND content_languages LIKE '%mri%'" \
    --outputFormat csv \
    --numOutputPartitions 10 \
    --outputCompression gzip \
    s3://commoncrawl/cc-index/table/cc-main/warc/ \
    hdfs:///user/vagrant/cc-mri-csv

----------------
Exception in thread "main" java.lang.RuntimeException: java.lang.ClassNotFoundException: Class org.apache.hadoop.fs.s3a.S3AFileSystem not found


https://stackoverflow.com/questions/39355354/spark-no-filesystem-for-scheme-https-cannot-load-files-from-amazon-s3
https://stackoverflow.com/questions/33356041/technically-what-is-the-difference-between-s3n-s3a-and-s3
"2018-01-10 Update Hadoop 3.0 has cut its s3: and s3n implementations: s3a is all you get. It is now significantly better than its predecessor and performs as least as good as the Amazon implementation. Amazon's "s3:" is still offered by EMR, which is their closed source client. Consult the EMR docs for more info."

1. https://stackoverflow.com/questions/30385981/how-to-access-s3a-files-from-apache-spark

"Having experienced first hand the difference between s3a and s3n - 7.9GB of data transferred on s3a was around ~7 minutes while 7.9GB of data on s3n took 73 minutes [us-east-1 to us-west-1 unfortunately in both cases; Redshift and Lambda being us-east-1 at this time] this is a very important piece of the stack to get correct and it's worth the frustration.

Here are the key parts, as of December 2015:

    Your Spark cluster will need a Hadoop version 2.x or greater. If you use the Spark EC2 setup scripts and maybe missed it, the switch for using something other than 1.0 is to specify --hadoop-major-version 2 (which uses CDH 4.2 as of this writing).

    You'll need to include what may at first seem to be an out of date AWS SDK library (built in 2014 as version 1.7.4) for versions of Hadoop as late as 2.7.1 (stable): aws-java-sdk 1.7.4. As far as I can tell using this along with the specific AWS SDK JARs for 1.10.8 hasn't broken anything.

    You'll also need the hadoop-aws 2.7.1 JAR on the classpath. This JAR contains the class org.apache.hadoop.fs.s3a.S3AFileSystem.

    In spark.properties you probably want some settings that look like this:

    spark.hadoop.fs.s3a.impl=org.apache.hadoop.fs.s3a.S3AFileSystem  
    spark.hadoop.fs.s3a.access.key=ACCESSKEY  
    spark.hadoop.fs.s3a.secret.key=SECRETKEY

I've detailed this list in more detail on a post I wrote as I worked my way through this process. In addition I've covered all the exception cases I hit along the way and what I believe to be the cause of each and how to fix them."


2. The classpath used by hadoop can be found by running the command (https://stackoverflow.com/questions/26748811/setting-external-jars-to-hadoop-classpath):
    hadoop classpath


3. Got hadoop-aws 2.7.6 jar
from https://mvnrepository.com/artifact/org.apache.hadoop/hadoop-aws/2.7.6
and put it into /home/vagrant


4. https://stackoverflow.com/questions/26748811/setting-external-jars-to-hadoop-classpath
https://stackoverflow.com/questions/28520821/how-to-add-external-jar-to-hadoop-job/54459211#54459211
vagrant@node1:~$ export LIBJARS=/home/vagrant/hadoop-aws-2.7.6.jar
vagrant@node1:~$ export HADOOP_CLASSPATH=`echo ${LIBJARS} | sed s/,/:/g`
vagrant@node1:~$ hadoop classpath

5. https://community.cloudera.com/t5/Community-Articles/HDP-2-4-0-and-Spark-1-6-0-connecting-to-AWS-S3-buckets/ta-p/245760
"Download the aws sdk for java https://aws.amazon.com/sdk-for-java/ Uploaded it to the hadoop directory. You should see the aws-java-sdk-1.10.65.jar in /usr/hdp/2.4.0.0-169/hadoop/"

I got version 1.11

[Can't find a spark.properties file, but this seems to contain spark specific properties:
$SPARK_HOME/conf/spark-defaults.conf

https://jaceklaskowski.gitbooks.io/mastering-apache-spark/spark-properties.html
"The default Spark properties file is $SPARK_HOME/conf/spark-defaults.conf that could be overriden using spark-submit with the --properties-file command-line option."]

Can SUDO COPY the 2 jar files hadoop-aws-2.7.6.jar and aws-java-sdk-1.11.616.jar to:
/usr/local/hadoop/share/hadoop/common/
(else /usr/local/hadoop/share/hadoop/hdfs/hadoop-aws-2.7.6.jar)

--------
schema
https://commoncrawl.s3.amazonaws.com/cc-index/table/cc-main/index.html

---------------
More examples to try:
https://github.com/commoncrawl/cc-warc-examples


A bit outdated?
https://www.journaldev.com/20342/apache-spark-example-word-count-program-java
https://www.journaldev.com/20261/apache-spark

--------

sudo apt-get install maven
(or sudo apt update
sudo apt install maven)
git clone https://github.com/commoncrawl/cc-index-table.git
cd cc-index-table
mvn package
vagrant@node1:~/cc-index-table$ ./src/script/convert_url_index.sh https://commoncrawl.s3.amazonaws.com/cc-index/collections/CC-MAIN-2019-30/indexes/cdx-00000.gz hdfs:///user/vagrant/cc-index-table




spark:
https://jaceklaskowski.gitbooks.io/mastering-apache-spark/spark-shell.html

============
Dr Bainbridge found the following vagrant file that will set up hadoop and spark presumably for cluster computing:

https://github.com/martinprobson/vagrant-hadoop-hive-spark

Vagrant:
    * Guide: https://www.vagrantup.com/intro/getting-started/index.html
    * Common cmds: https://blog.ipswitch.com/5-vagrant-commands-you-need-to-know
    * vagrant reload = vagrant halt + vagrant up https://www.vagrantup.com/docs/cli/reload.html
    * https://stackoverflow.com/questions/46903623/how-to-use-firefox-ui-in-vagrant-box
    * https://stackoverflow.com/questions/22651399/how-to-install-firefox-in-precise64-vagrant-box
      sudo apt-get -y install firefox
    * vagrant install emacs: https://medium.com/@AnnaJS15/getting-started-with-virtualbox-and-vagrant-8d98aa271d2a

    * hadoop conf: sudo vi /usr/local/hadoop-2.7.6/etc/hadoop/mapred-site.xml
    * https://data-flair.training/forums/topic/mkdir-cannot-create-directory-data-name-node-is-in-safe-mode/
---
==> node1: Forwarding ports...
    node1: 8080 (guest) => 8081 (host) (adapter 1)
    node1: 8088 (guest) => 8089 (host) (adapter 1)
    node1: 9083 (guest) => 9084 (host) (adapter 1)
    node1: 4040 (guest) => 4041 (host) (adapter 1)
    node1: 18888 (guest) => 18889 (host) (adapter 1)
    node1: 16010 (guest) => 16011 (host) (adapter 1)
    node1: 22 (guest) => 2200 (host) (adapter 1)
==> node1: Running 'pre-boot' VM customizations...


==> node1: Checking for guest additions in VM...
    node1: The guest additions on this VM do not match the installed version of
    node1: VirtualBox! In most cases this is fine, but in rare cases it can
    node1: prevent things such as shared folders from working properly. If you see
    node1: shared folder errors, please make sure the guest additions within the
    node1: virtual machine match the version of VirtualBox you have installed on
    node1: your host and reload your VM.
    node1: 
    node1: Guest Additions Version: 5.1.38
    node1: VirtualBox Version: 5.2

------------