Setup a folder inside a repo with a specific commit of that repo.
git worktree add [-f] [--detach] [--checkout] [--lock] [-b ] []
Setup a folder inside a repo with a specific commit of that repo.
git worktree add [-f] [--detach] [--checkout] [--lock] [-b ] []
export HADOOP_VERSION=2.9.1 | |
export SPARK_VERSION=2.3.2 | |
export AWS_ACCOUNT_ID=<your numeric AWS account id> | |
export ECR_REGION=us-east-1 | |
# Fetch and extract the spark source | |
curl -L "https://archive.apache.org/dist/spark/spark-${SPARK_VERSION}/spark-${SPARK_VERSION}.tgz" | tar -xzvf - | |
cd "spark-${SPARK_VERSION}" | |
# set maven opts according to https://spark.apache.org/docs/latest/building-spark.html | |
export MAVEN_OPTS="-Xmx2g -XX:ReservedCodeCacheSize=512m" |
UPDATED 22.11.2022
It's been two years since the last update, so here's the updated working script as per the comments below.
Thanks to BryanHaley for this.
setInterval(function () {
video = document.getElementsByTagName('ytd-playlist-video-renderer')[0];
video.querySelector('#primary button[aria-label="Action menu"]').click();
FROM rustlang/rust:nightly as builder | |
WORKDIR /app/src | |
RUN USER=root cargo new --bin ht | |
COPY Cargo.toml Cargo.lock ./ht/ | |
WORKDIR /app/src/ht | |
RUN cargo build --release | |
COPY ./ ./ | |
RUN cargo build --release |
# Below are the dependencies required for installing the common combination of numpy, scipy, pandas and matplotlib | |
# in an Alpine based Docker image. | |
FROM alpine:3.4 | |
RUN echo "http://dl-8.alpinelinux.org/alpine/edge/community" >> /etc/apk/repositories | |
RUN apk --no-cache --update-cache add gcc gfortran python python-dev py-pip build-base wget freetype-dev libpng-dev openblas-dev | |
RUN ln -s /usr/include/locale.h /usr/include/xlocale.h | |
RUN pip install numpy scipy pandas matplotlib | |
package de.tdlabs.keycloak.client; | |
import com.fasterxml.jackson.databind.ObjectMapper; | |
import org.keycloak.OAuth2Constants; | |
import org.keycloak.RSATokenVerifier; | |
import org.keycloak.admin.client.Keycloak; | |
import org.keycloak.admin.client.KeycloakBuilder; | |
import org.keycloak.common.VerificationException; | |
import org.keycloak.jose.jws.JWSHeader; | |
import org.keycloak.representations.AccessToken; |
flatMap
, especially if the following operation will result in high memory usage. The flatMap
op usually results in a DataFrame with a [much] larger number of rows, yet the number of partitions will remain the same. Thus, if a subsequent op causes a large expansion of memory usage (i.e. converting a DataFrame of indices to a DataFrame of large Vectors), the memory usage per partition may become too high. In this case, it is beneficial to repartition the output of flatMap
to a number of partitions that will safely allow for appropriate partition memory sizes, based upon theRegion Code | Region Name | Availability Zones |
---|---|---|
us-east-1* | N. Virginia | us-east-1a us-east-1b us-east-1c us-east-1d us-east-1e |
us-east-2 | Ohio | us-east-2a us-east-2b us-east-2c |
us-west-1* | N. California | us-west-1a us-west-1b us-west-1c |
us-west-2 | Oregon | us-west-2a us-west-2b us-west-2c |
eu-west-1 | Ireland | eu-west-1a eu-west-1b eu-west-1c |
eu-central-1 | Frankfurt | eu-central-1a eu-central-1b |