Docker Management using Portainer

Portainer is a lightweight management UI that allows easy management of Docker environments, including creating, deploying, and managing containers, services, and stacks. It is particularly useful for those who are new to Docker or those who prefer a visual interface over command-line management.

To install Portainer with a persistent container, you can follow these steps:

• Pull the Portainer image: docker pull portainer/portainer
• Create a directory for Portainer data: mkdir -p /mnt/docker/portainer/data
• Create a Docker service for Portainer with the following command:  

docker service create \ --name portainer \ --publish 9090:9000 \ --constraint 'node.role == manager' \ --mount type=bind,src=/mnt/docker/portainer/data,dst=/data \ --mount type=bind,src=/var/run/docker.sock,dst=/var/run/docker.sock \ portainer/portainer \ -H unix:///var/run/docker.sock

 

the above command will create a new Docker service named "portainer" with a published port of 9090, mounted volume for persistent data, and a constraint for the node role of "manager".

• Access the Portainer UI by visiting the IP address or hostname of the Docker swarm manager node on port 9090 in a web browser.
• Create a new user account and start managing your Docker environment using the Portainer UI.

Access the Portainer UI by visiting the IP address or hostname of the Docker swarm manager node on port 9090 in a web browser.

Qubole load CSV with spark

This is a code snippet using Spark on Qubole to load a CSV file into a DataFrame, register it as a temporary table, and create a permanent table from the data in the temporary table.

The first line of code reads the CSV file from an S3 location into a DataFrame. The options set for the format, delimiter, header, and inferSchema specify how the CSV file should be read and parsed.

val df = sqlContext.read.format("com.databricks.spark.csv")
                    .option("delimiter", "|")
                    .option("header", "true")
                    .option("inferSchema", "true")
                    .load("s3://*****.CSV")

The second line of code registers the DataFrame as a temporary table, which can be used for querying.

df.registerTempTable("temp-table")

The third line of code creates a permanent table in a specified database by executing an SQL query on the temporary table. The query selects all the columns and rows from the temporary table and creates a new table with the same data in the specified database.

sqlContext.sql("""
create table database.table as
select * from temp-table
""")

Increases swap in azure linux machine

In Azure to create a swap file in the directory that's defined by the ResourceDisk.MountPoint parameter, you can update the /etc/waagent.conf file by setting the following three parameters:

ResourceDisk.Format=y
ResourceDisk.EnableSwap=y
ResourceDisk.SwapSizeMB=xx

Note The xx placeholder represents the desired number of megabytes (MB) for the swap file.
Restart the WALinuxAgent service by running one of the following commands, depending on the system in question:

Ubuntu: service walinuxagent restart
Red Hat/Centos: service waagent restart

Run one of the following commands to show the new swap apace that's being used after the restart:

dmesg | grep swap
swapon -s
cat /proc/swaps
file /mnt/resource/swapfile
free| grep -i swap

If the swap file isn't created, you can restart the virtual machine by using one of the following commands:

shutdown -r now
init 6