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Ravi Teja Sikhakolli ravi-tejarockon

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ravi-tejarockon / cloudfrontFN.js
Last active November 3, 2023 19:50
cloudfront
function handler(event) {
// Redirect from apex to subdomain (e.g. www).
var request = event.request;
if (request.headers.host) {
var host = request.headers.host.value;
if (host === '<APEX_DOMAIN_HERE>') {
return {
statusCode: 301,
@ravi-tejarockon
ravi-tejarockon / Books.md
Last active June 17, 2020 06:30
Programming Books
@ravi-tejarockon
ravi-tejarockon / Notes
Last active April 10, 2020 13:42
Apache Kafka Certification by Confluent
Certification in Kafka Confluent -- Notes: [1]
There are 2 certifications provided by Confluent on Kafka i.e.
Note:
-- There are available PDFs as uploaded in this below repo, Please read.
https://github.com/ravi-tejarockon/kafka-certification
-- There are few courses available to understand and attempt exam, even though they're not mandatory but will help us to get through exam.
1. Confluent Certified Developer for Apache Kafka (CCDAK)
-- Practice & Training is available by Stephen Mareek for this Certification, he is expert in Kafka [3]
-- His guidance is given by blog [3]
@ravi-tejarockon
ravi-tejarockon / structured_wc_kafka.py
Created February 28, 2019 15:54
Spark & Kafka Integration - Spark Structured Streaming Streaming (Spark 2.x)
# Running locations:
# Exeucing Command: bin\spark-submit --packages org.apache.spark:spark-sql-kafka-0-10_2.11 <location_of_code>\structured_kafka_wc.py localhost:2181 <topic_name>
# Location to Execute: <location_of_spark_bin>
# https://github.com/apache/spark/blob/v2.3.1/examples/src/main/python/sql/streaming/structured_kafka_wordcount.py
from __future__ import print_function
import sys
import os
@ravi-tejarockon
ravi-tejarockon / kafkaPySpark.py
Created February 28, 2019 15:50
Spark & Kafka Integration - Spark Streaming (Spark 1.6.3)
# Running locations:
# Exeucing Command: bin\spark-submit --packages org.apache.spark:spark-streaming-kafka_2.10:1.6.3 <location_of_code>/kafkaPySpark.py localhost:2181 <topic_name>
# Location to Execute: <location_of_spark_bin>
from __future__ import print_function
import os
import sys
from pyspark import SparkContext
from pyspark.streaming import StreamingContext