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Step 1 - Create .crt file | |
cat domainname.crt domainname.ca-bundle > domainname-ssl-bundle.crt | |
Step 2- | |
Add lines for ssl_certificate in nginx configuration | |
server { | |
listen 80 default_server; |
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# This script will take backup of ambari server and move to S3 | |
# Make sure you have s3cmd installed and configured https://github.com/s3tools/s3cmd | |
# Customize it according to your need | |
#!/bin/bash | |
USERNAME=$1 | |
export PGPASSWORD=$2 | |
DB=ambari |
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# Include Kafka binaries in the path | |
export PATH=$PATH:/usr/hdp/current/kafka-broker/bin | |
# Create the topic | |
# Replace localhost with the hostname of node where zookeeper server is running. | |
# Replace test with your topic name | |
kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic test | |
# Check if topic is created | |
kafka-topics.sh --list --zookeeper localhost:2181 |
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# Clone CloudxLab BigData repository | |
git clone https://github.com/cloudxlab/bigdata.git | |
# If already cloned then update the repository | |
cd ~/bigdata && git pull origin master | |
# Code is inside spark/examples/streaming/word_count_kafka |
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from tensorflow.contrib.slim.nets import inception | |
import tensorflow.contrib.slim as slim | |
X = tf.placeholder(tf.float32, shape=[None, 299, 299, 3]) | |
with slim.arg_scope(inception.inception_v3_arg_scope()): | |
logits, end_points = inception.inception_v3( | |
X, num_classes=1001, is_training=False | |
) | |
predictions = end_points["Predictions"] | |
saver = tf.train.Saver() |