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SPARK VAGRANT FOR MAC MAC OS
SPARK VAGRANT FOR MAC 64 BIT
SPARK VAGRANT FOR MAC SOFTWARE
SPARK VAGRANT FOR MAC PASSWORD
SPARK VAGRANT FOR MAC PLUS

Logfiles are generated in /var/log/ipnb inside the VM: Sudo systemctl (start | stop | restart) notebookįor diagnostics, in addition to the messages appearing directly on notebooks, (start/stop/restart) in a VM console session (see below) via: The Jupyter notebook server starts automatically. Spark SQL for its metastore & tables (so it should survive to changes in

Finally, the vmfiles/hive subdirectory is the place configured in.

A fewĮxample mini-notebooks are already provided there. Host folder), so to add notebooks place them in that subdirectory. Vmfiles/IPNB subdirectory (it appears under the notebook interface as the

Furthermore, the notebook server is configured to browse the files in the.

The VM as the /vagrant directory, so anything in that subfolder can be

The vmfiles subfolder in the host is configured to be mounted inside.

The additional files in the ZIP create a layout for sharing content between The Vagrantfile (unless changed before installation, it will be vmuser)

SPARK VAGRANT FOR MAC PASSWORD

Using the notebook interface will require the access password defined in The network can also connect to it (unless the host computer has a firewall that By default it is also accessible externally, i.e. Once installation finishes, a notebook server will be running onĪccess it. Problem as long as there is a working Internet connection.

The base box (the one that was created by the baseĭownloadable when provisioning this VM. Then the VM will be started and provisioned. Repository (this takes time, depending on your network bandwidth, but it is Vagrant should launch the process and download the base box from the public Located and execute a vagrant up command. Open a console/terminal, move ( cd) to the folder where the Vagrantfile is Happily work with no changes to the Vagrantfile) Note that no customization is needed to make the VM work (i.e. Another configurable value is the notebookĪccess password (in the vm_password variable). Virtual Machine and, if access to a remote Spark cluster is sought, the Specially interesting might be the amount of RAM/CPUs assigned to the Options at the top of the file see the relevant comments. If desired, open the Vagrantfile with a text editor and customize the Spaces (since sometimes it causes problems). Make sure to use a disk or partition with the mentioned 10 GB of free space.Īlso, in Windows it might be advisable to avoid using a folder name with Repository or by downloading and extracting all files in the packaged

Vagrant 2.0 or above (if possible, use the latest version available)Ĭopy the Vagrantfile + examples into the computer, either by cloning the.

Virtualbox 6.0 or above (if possible, use the latest version available).

Software: The following must be installed in the computer:.

Not work with M1 & M2 Mac computers, it needs an Intel-based computer

SPARK VAGRANT FOR MAC MAC OS

Linux 64 bits (Ubuntu, RedHat/CentOS, etc) or Mac OS X.

Hardware & OS: A computer with enough free RAM (at least 2 GB is advisable),Īnd around 10 GB of hard disk space, with a 64-bit Windows (7 or above),.

Saving it will make it work in future executions. Once done, the change is stored in the notebook, so They can be made to work by changing its kernel (use the option in the menubar) (or with former versions of this VM) will not work initially. Hence Spark Python Notebooks that were created elsewhere To develop notebooks in Python for Spark, the Pyspark (Py 3) kernel must be Important: the default Python kernel for notebooks is not Spark-aware.

A notebook startup daemon script with facilities to configure Spark execution mode.

Spark notebook Kernels for Python 3.10, Scala ( Almond) and R ( IRKernel), in addition to the default "plain" (i.e.

SPARK VAGRANT FOR MAC PLUS

Plus SparkR & sparklyr for interaction with Spark.

R 4.2 with a few packages installed (rmarkdown, magrittr, dplyr, tidyr, data.table, ggplot2, caret, plus their dependencies).

A virtualenv for Python 3.10 with a scientific Python stack (scipy, numpy, matplotplib, pandas, statmodels, scikit-learn, gensim, xgboost, networkx, seaborn, pylucene and a few others) plus IPython 8 + Jupyter notebook.

The repository also contains a number of small example notebooks.

R (with SparkR available, though not loaded by default).

Scala 2.12 (with the capability of connecting to Spark).

Pyspark (Python 3.10 + libraries + Spark),.

Python 3.10 (plain Python, with additional libraries such as NumPy, SciPy,.

It allows creating notebooks with four different kernels:

On top of that, itĬonfigures and launches a Jupyter Notebook process, exported as an HTTP service

SPARK VAGRANT FOR MAC SOFTWARE

The needed software packages, on an Ubuntu 22.04 box). This instance builds on the spark-base64 VM (which already provides all

SPARK VAGRANT FOR MAC 64 BIT

A 64 bit virtual machine for Machine Learning/Data Science tasks.