From 6868fb46d07cdad862f65ed183104db1c3773783 Mon Sep 17 00:00:00 2001 From: Kevin Bates Date: Tue, 17 Aug 2021 10:54:34 -0700 Subject: [PATCH] Prepare release 2.5.1 --- Makefile | 2 +- docs/source/docker.md | 4 ++-- docs/source/getting-started.md | 2 +- docs/source/kernel-distributed.md | 4 ++-- docs/source/kernel-kubernetes.md | 6 +++--- docs/source/kernel-spark-standalone.md | 16 ++++++++-------- docs/source/kernel-yarn-client-mode.md | 16 ++++++++-------- docs/source/kernel-yarn-cluster-mode.md | 18 +++++++++--------- enterprise_gateway/_version.py | 2 +- .../helm/enterprise-gateway/Chart.yaml | 2 +- 10 files changed, 36 insertions(+), 36 deletions(-) diff --git a/Makefile b/Makefile index 1a84ca0a4..bebf49c2d 100644 --- a/Makefile +++ b/Makefile @@ -12,7 +12,7 @@ SA?=source activate ENV:=enterprise-gateway-dev SHELL:=/bin/bash -VERSION?=2.5.0 +VERSION?=2.5.1 SPARK_VERSION?=2.4.6 ifeq (dev, $(findstring dev, $(VERSION))) diff --git a/docs/source/docker.md b/docs/source/docker.md index 2ed8353b3..b2940261b 100644 --- a/docs/source/docker.md +++ b/docs/source/docker.md @@ -65,7 +65,7 @@ Users that do not wish to extend an existing kernel image must be cognizant of a 2. Is the base image one from [Jupyter Docker-stacks](https://github.com/jupyter/docker-stacks)? #### Requirements for Custom Kernel Images -Custom kernel images require some support files from the Enterprise Gateway repository. These are packaged into a tar file for each release starting in `2.5.0`. This tar file (named `jupyter_enterprise_gateway_kernel_image_files-VERSION.tar.gz`) is composed of a few files - one bootstrap script and a kernel launcher (one per kernel type). +Custom kernel images require some support files from the Enterprise Gateway repository. These are packaged into a tar file for each release starting in `2.5.1`. This tar file (named `jupyter_enterprise_gateway_kernel_image_files-VERSION.tar.gz`) is composed of a few files - one bootstrap script and a kernel launcher (one per kernel type). ##### Bootstrap-kernel.sh Enterprise Gateway provides a single [bootstrap-kernel.sh](https://github.com/jupyter/enterprise_gateway/blob/master/etc/kernel-launchers/bootstrap/bootstrap-kernel.sh) script that handles the three kernel languages supported out of the box - Python, R, and Scala. When a kernel image is started by Enterprise Gateway, parameters used within the bootstrap-kernel.sh script are conveyed via environment variables. The bootstrap script is then responsible for validating and converting those parameters to meaningful arguments to the appropriate launcher. @@ -119,7 +119,7 @@ If your base image is not from docker-stacks, it is recommended that you NOT run Aside from configuring the image user, all other aspects of customization are the same. In this case, we'll use the tensorflow-gpu image and convert it to be usable via Enterprise Gateway as a custom kernel image. Note that because this image didn't have `wget` we used `curl` to download the supporting kernel-image files. ```dockerfile -FROM tensorflow/tensorflow:2.5.0-gpu-jupyter +FROM tensorflow/tensorflow:2.5.1-gpu-jupyter USER root diff --git a/docs/source/getting-started.md b/docs/source/getting-started.md index 175b3dd5f..17ecb83f6 100644 --- a/docs/source/getting-started.md +++ b/docs/source/getting-started.md @@ -148,7 +148,7 @@ Note that because the Apache Toree kernel, and its supporting libraries, will be #### Sample kernelspecs -We provide sample kernel configuration and launcher tar files as part of [each release](https://github.com/jupyter/enterprise_gateway/releases) (e.g. [jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz](https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz)) that can be extracted and modified to fit your configuration. +We provide sample kernel configuration and launcher tar files as part of [each release](https://github.com/jupyter/enterprise_gateway/releases) (e.g. [jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz](https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz)) that can be extracted and modified to fit your configuration. For information about how to build your own kernel-based docker image for use by Enterprise Gateway see [Custom kernel images](docker.html#custom-kernel-images). diff --git a/docs/source/kernel-distributed.md b/docs/source/kernel-distributed.md index 95e4b9606..b65021ec1 100644 --- a/docs/source/kernel-distributed.md +++ b/docs/source/kernel-distributed.md @@ -9,9 +9,9 @@ The following sample kernelspecs are currently available on Distributed mode: Install the `python_distributed` kernelspec on all nodes. ``` Bash -wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz +wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz KERNELS_FOLDER=/usr/local/share/jupyter/kernels -tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz --strip 1 --directory $KERNELS_FOLDER/python_distributed/ python_distributed/ +tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz --strip 1 --directory $KERNELS_FOLDER/python_distributed/ python_distributed/ ``` The `python_distributed` kernelspec uses `DistributedProcessProxy` which is responsible for the launch and management of kernels distributed across and explicitly defined set of hosts using ssh. Hosts are determined via a round-robin algorithm (that we should make pluggable someday). diff --git a/docs/source/kernel-kubernetes.md b/docs/source/kernel-kubernetes.md index e054eda32..6bf4402b1 100644 --- a/docs/source/kernel-kubernetes.md +++ b/docs/source/kernel-kubernetes.md @@ -523,7 +523,7 @@ By default, _vanilla_ kernels use a value of `none` for the spark context initia When the kernel is intended to target _Spark-on-kubernetes_, its launch is very much like kernels launched in YARN _cluster mode_, albeit with a completely different set of parameters. Here's an example `SPARK_OPTS` string value which best conveys the idea: ``` - "SPARK_OPTS": "--master k8s://https://${KUBERNETES_SERVICE_HOST}:${KUBERNETES_SERVICE_PORT} --deploy-mode cluster --name ${KERNEL_USERNAME}-${KERNEL_ID} --conf spark.kubernetes.driver.label.app=enterprise-gateway --conf spark.kubernetes.driver.label.kernel_id=${KERNEL_ID} --conf spark.kubernetes.executor.label.app=enterprise-gateway --conf spark.kubernetes.executor.label.kernel_id=${KERNEL_ID} --conf spark.kubernetes.driver.docker.image=${KERNEL_IMAGE} --conf spark.kubernetes.executor.docker.image=kubespark/spark-executor-py:v2.5.0-kubernetes-0.5.0 --conf spark.kubernetes.submission.waitAppCompletion=false", + "SPARK_OPTS": "--master k8s://https://${KUBERNETES_SERVICE_HOST}:${KUBERNETES_SERVICE_PORT} --deploy-mode cluster --name ${KERNEL_USERNAME}-${KERNEL_ID} --conf spark.kubernetes.driver.label.app=enterprise-gateway --conf spark.kubernetes.driver.label.kernel_id=${KERNEL_ID} --conf spark.kubernetes.executor.label.app=enterprise-gateway --conf spark.kubernetes.executor.label.kernel_id=${KERNEL_ID} --conf spark.kubernetes.driver.docker.image=${KERNEL_IMAGE} --conf spark.kubernetes.executor.docker.image=kubespark/spark-executor-py:v2.5.1-kubernetes-0.5.0 --conf spark.kubernetes.submission.waitAppCompletion=false", ``` Note that each of the labels previously discussed are also applied to the _driver_ and _executor_ pods. @@ -595,9 +595,9 @@ From anywhere with Helm cluster access, create the service and deployment by run ```bash helm upgrade --install --atomic --namespace enterprise-gateway enterprise-gateway etc/kubernetes/helm/enterprise-gateway ``` -the helm chart tarball is also accessible as an asset on our [release](https://github.com/jupyter/enterprise_gateway/releases/tag/v2.5.0) page: +the helm chart tarball is also accessible as an asset on our [release](https://github.com/jupyter/enterprise_gateway/releases/tag/v2.5.1) page: ```bash -helm install --name enterprise-gateway --atomic --namespace enterprise-gateway https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_helm-2.5.0.tgz +helm install --name enterprise-gateway --atomic --namespace enterprise-gateway https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_helm-2.5.1.tgz ``` ##### Configuration diff --git a/docs/source/kernel-spark-standalone.md b/docs/source/kernel-spark-standalone.md index b90a1843d..ac9def600 100644 --- a/docs/source/kernel-spark-standalone.md +++ b/docs/source/kernel-spark-standalone.md @@ -23,14 +23,14 @@ EG_REMOTE_HOSTS=elyra-node-1.fyre.ibm.com,elyra-node-2.fyre.ibm.com,elyra-node-3 Although Enterprise Gateway does not currently provide sample kernelspecs for Spark standalone, here are the steps necessary to convert a yarn_client kernelspec to standalone. For each supported Jupyter Kernel, we have provided sample kernel configurations and launchers as part of the release -[jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz](https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz). +[jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz](https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz). Considering we would like to enable the IPython Kernel that comes pre-installed with Anaconda to run on Spark Standalone, we would have to copy the sample configuration folder **spark_python_yarn_client** to where the Jupyter kernels are installed (e.g. jupyter kernelspec list) and rename it to **spark_python_spark_standalone*** ``` Bash -wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz +wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz SCALA_KERNEL_DIR="$(jupyter kernelspec list | grep -w "python3" | awk '{print $2}')" KERNELS_FOLDER="$(dirname "${SCALA_KERNEL_DIR}")" tar -zxvf enterprise_gateway_kernelspecs.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_python_yarn_client/ spark_python_yarn_client/ @@ -85,9 +85,9 @@ Follow the steps below to install/configure the Toree kernel: Considering we would like to enable the Scala Kernel to run on YARN Cluster and Client mode we would have to copy the sample configuration folder **spark_scala_yarn_client** to where the Jupyter kernels are installed (e.g. jupyter kernelspec list) ``` Bash -wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz +wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz KERNELS_FOLDER=/usr/local/share/jupyter/kernels -tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_scala_yarn_client/ spark_scala_yarn_client/ +tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_scala_yarn_client/ spark_scala_yarn_client/ mv $KERNELS_FOLDER/spark_scala_yarn_client $KERNELS_FOLDER/spark_scala_spark_standalone ``` @@ -102,9 +102,9 @@ The IPython kernel comes pre-installed with Anaconda and we have tested with its Considering we would like to enable the IPython kernel to run on YARN Cluster and Client mode we would have to copy the sample configuration folder **spark_python_yarn_client** to where the Jupyter kernels are installed (e.g. jupyter kernelspec list) ``` Bash -wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz +wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz KERNELS_FOLDER=/usr/local/share/jupyter/kernels -tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_python_yarn_client/ spark_python_yarn_client/ +tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_python_yarn_client/ spark_python_yarn_client/ mv $KERNELS_FOLDER/spark_python_yarn_client $KERNELS_FOLDER/spark_python_spark_standalone ``` @@ -137,9 +137,9 @@ ls $ANACONDA_HOME/lib/R/library Considering we would like to enable the IRkernel to run on YARN Cluster and Client mode we would have to copy the sample configuration folder **spark_R_yarn_client** to where the Jupyter kernels are installed (e.g. jupyter kernelspec list) ``` Bash -wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz +wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz KERNELS_FOLDER=/usr/local/share/jupyter/kernels -tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_R_yarn_client/ spark_R_yarn_client/ +tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_R_yarn_client/ spark_R_yarn_client/ mv $KERNELS_FOLDER/spark_R_yarn_client $KERNELS_FOLDER/spark_R_spark_standalone ``` diff --git a/docs/source/kernel-yarn-client-mode.md b/docs/source/kernel-yarn-client-mode.md index de81bf690..f909bb52d 100644 --- a/docs/source/kernel-yarn-client-mode.md +++ b/docs/source/kernel-yarn-client-mode.md @@ -27,14 +27,14 @@ EG_REMOTE_HOSTS=elyra-node-1.fyre.ibm.com,elyra-node-2.fyre.ibm.com,elyra-node-3 ``` For each supported Jupyter Kernel, we have provided sample kernel configurations and launchers as part of the release -[jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz](https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz). +[jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz](https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz). Considering we would like to enable the IPython Kernel that comes pre-installed with Anaconda to run on Yarn Client mode, we would have to copy the sample configuration folder **spark_python_yarn_client** to where the Jupyter kernels are installed (e.g. jupyter kernelspec list) ``` Bash -wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz +wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz SCALA_KERNEL_DIR="$(jupyter kernelspec list | grep -w "python3" | awk '{print $2}')" KERNELS_FOLDER="$(dirname "${SCALA_KERNEL_DIR}")" tar -zxvf enterprise_gateway_kernelspecs.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_python_yarn_client/ spark_python_yarn_client/ @@ -82,9 +82,9 @@ Follow the steps below to install/configure the Toree kernel: Considering we would like to enable the Scala Kernel to run on YARN Cluster and Client mode we would have to copy the sample configuration folder **spark_scala_yarn_client** to where the Jupyter kernels are installed (e.g. jupyter kernelspec list) ``` Bash -wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz +wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz KERNELS_FOLDER=/usr/local/share/jupyter/kernels -tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_scala_yarn_client/ spark_scala_yarn_client/ +tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_scala_yarn_client/ spark_scala_yarn_client/ ``` For more information about the Scala kernel, please visit the [Apache Toree](https://toree.apache.org/) page. @@ -98,9 +98,9 @@ The IPython kernel comes pre-installed with Anaconda and we have tested with its Considering we would like to enable the IPython kernel to run on YARN Cluster and Client mode we would have to copy the sample configuration folder **spark_python_yarn_client** to where the Jupyter kernels are installed (e.g. jupyter kernelspec list) ``` Bash -wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz +wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz KERNELS_FOLDER=/usr/local/share/jupyter/kernels -tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_python_yarn_client/ spark_python_yarn_client/ +tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_python_yarn_client/ spark_python_yarn_client/ ``` For more information about the IPython kernel, please visit the [IPython kernel](https://ipython.readthedocs.io/en/stable/) page. @@ -132,9 +132,9 @@ ls $ANACONDA_HOME/lib/R/library Considering we would like to enable the IRkernel to run on YARN Cluster and Client mode we would have to copy the sample configuration folder **spark_R_yarn_client** to where the Jupyter kernels are installed (e.g. jupyter kernelspec list) ``` Bash -wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz +wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz KERNELS_FOLDER=/usr/local/share/jupyter/kernels -tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_R_yarn_client/ spark_R_yarn_client/ +tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_R_yarn_client/ spark_R_yarn_client/ ``` For more information about the iR kernel, please visit the [IRkernel](https://irkernel.github.io/) page. diff --git a/docs/source/kernel-yarn-cluster-mode.md b/docs/source/kernel-yarn-cluster-mode.md index 3f8409143..5130cd605 100644 --- a/docs/source/kernel-yarn-cluster-mode.md +++ b/docs/source/kernel-yarn-cluster-mode.md @@ -28,16 +28,16 @@ EG_ALT_YARN_ENDPOINT=http://${ALT_YARN_RESOURCE_MANAGER_FQDN}:8088/ws/v1/cluster ### Configuring Kernels for YARN Cluster mode -For each supported Jupyter Kernel, we have provided sample kernel configurations and launchers as part of the release [jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz](https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz). +For each supported Jupyter Kernel, we have provided sample kernel configurations and launchers as part of the release [jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz](https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz). Considering we would like to enable the IPython Kernel that comes pre-installed with Anaconda to run on Yarn Cluster mode, we would have to copy the sample configuration folder **spark_python_yarn_cluster** to where the Jupyter kernels are installed (e.g. jupyter kernelspec list) ``` Bash -wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz +wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz SCALA_KERNEL_DIR="$(jupyter kernelspec list | grep -w "python3" | awk '{print $2}')" KERNELS_FOLDER="$(dirname "${SCALA_KERNEL_DIR}")" mkdir $KERNELS_FOLDER/spark_python_yarn_cluster/ -tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_python_yarn_cluster/ spark_python_yarn_cluster/ +tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_python_yarn_cluster/ spark_python_yarn_cluster/ ``` After that, you should have a `kernel.json` that looks similar to the one below: @@ -80,9 +80,9 @@ Follow the steps below to install/configure the Toree kernel: Considering we would like to enable the Scala Kernel to run on YARN Cluster and Client mode we would have to copy the sample configuration folder **spark_scala_yarn_cluster** to where the Jupyter kernels are installed (e.g. jupyter kernelspec list) ``` Bash -wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz +wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz KERNELS_FOLDER=/usr/local/share/jupyter/kernels -tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_scala_yarn_cluster/ spark_scala_yarn_cluster/ +tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_scala_yarn_cluster/ spark_scala_yarn_cluster/ ``` For more information about the Scala kernel, please visit the [Apache Toree](https://toree.apache.org/) page. @@ -96,9 +96,9 @@ The IPython kernel comes pre-installed with Anaconda and we have tested with its Considering we would like to enable the IPython kernel to run on YARN Cluster and Client mode we would have to copy the sample configuration folder **spark_python_yarn_cluster** to where the Jupyter kernels are installed (e.g. jupyter kernelspec list) ``` Bash -wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz +wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz KERNELS_FOLDER=/usr/local/share/jupyter/kernels -tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_python_yarn_cluster/ spark_python_yarn_cluster/ +tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_python_yarn_cluster/ spark_python_yarn_cluster/ ``` For more information about the IPython kernel, please visit the [IPython kernel](https://ipython.readthedocs.io/en/stable/) page. @@ -130,9 +130,9 @@ ls $ANACONDA_HOME/lib/R/library Considering we would like to enable the IRkernel to run on YARN Cluster and Client mode we would have to copy the sample configuration folder **spark_R_yarn_cluster** to where the Jupyter kernels are installed (e.g. jupyter kernelspec list) ``` Bash -wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.0/jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz +wget https://github.com/jupyter/enterprise_gateway/releases/download/v2.5.1/jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz KERNELS_FOLDER=/usr/local/share/jupyter/kernels -tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.0.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_R_yarn_cluster/ spark_R_yarn_cluster/ +tar -zxvf jupyter_enterprise_gateway_kernelspecs-2.5.1.tar.gz --strip 1 --directory $KERNELS_FOLDER/spark_R_yarn_cluster/ spark_R_yarn_cluster/ ``` For more information about the iR kernel, please visit the [IRkernel](https://irkernel.github.io/) page. diff --git a/enterprise_gateway/_version.py b/enterprise_gateway/_version.py index 1f8783c6f..59f9da224 100644 --- a/enterprise_gateway/_version.py +++ b/enterprise_gateway/_version.py @@ -3,4 +3,4 @@ # Copyright (c) Jupyter Development Team. # Distributed under the terms of the Modified BSD License. -__version__ = '2.5.0' +__version__ = '2.5.1' diff --git a/etc/kubernetes/helm/enterprise-gateway/Chart.yaml b/etc/kubernetes/helm/enterprise-gateway/Chart.yaml index fade8fc2b..c655df71e 100644 --- a/etc/kubernetes/helm/enterprise-gateway/Chart.yaml +++ b/etc/kubernetes/helm/enterprise-gateway/Chart.yaml @@ -1,6 +1,6 @@ name: enterprise-gateway description: A helm chart to deploy Jupyter Enterprise Gateway -version: 2.5.0 +version: 2.5.1 apiVersion: v1 icon: https://avatars1.githubusercontent.com/u/7388996?s=200&v=4 home: https://jupyter.org/enterprise_gateway