singhabhinav

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()

singhabhinav

# 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

singhabhinav

# 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

singhabhinav

# 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

singhabhinav

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;