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Python Program: JSON to CSV Conversion

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JavaScript object notion is also called JSON file, it's data you can write to a CSV file. Here's a sample python logic for your ready reference.  You can write a simple python program by importing the JSON, and CSV packages. This is your first step. It is helpful to use all the JSON methods in your python logic. That means the required package is JSON. So far, so good. In the next step, I'll show you how to write a Python program. You'll also find each term explained. What is JSON File JSON is key value pair file. The popular use of JSON file is to transmit data between heterogeneous applications. Python supports JSON file. What is CSV File The CSV is comma separated file. It is popularly used to send and receive data. How to Write JSON file data to a CSV file Here the JSON data that has written to CSV file. It's simple method and you can use for CSV file conversion use. import csv, json json_string = '[{"value1": 1, "value2": 2,"value3

How to Monitor Kafka-stream's Performance

Kafka Streams API is a part of Kafka, it goes without saying that monitoring your application will require some monitoring of Kafka as well.

Performance


The consumer and producer performance is one of the fundamental performance concerns for a producer and consumer.
 

Stream performance


The Kafka data flow diagram



Kafka data flow diagram


What is lag


For producers, we care mostly about how fast the producer is sending messages to the broker. Obviously, the higher the throughput, the better.

For consumers, we’re also concerned with performance, or how fast we can read messages from a broker.

we care about how much and how fast our producers can publish to a broker, and we simultaneously care about how quickly our consumers can read those messages from the broker. The difference between how fast the producers place records on the broker and when consumers read those messages is called consumer lag


How to check consumer lag


To check for consumer lag, Kafka provides a convenient command-line tool, kafka-consumer-groups.sh, found in the <kafka-install-dir>/bin directory. The script has a few options, but here we’ll focus on the list and describe options. These two options will give you the information you need about consumer group performance.

List command

<kafka-install-dir>/bin/kafka-consumer-groups.sh \ --bootstrap-server localhost:9092 \ --list


Describe command

<kafka-install-dir>/bin/kafka-consumer-groups.sh \ --bootstrap-server localhost:9092 \ --group <GROUP-NAME> \ --describe


How to trace problem

  • A small lag or one that stays constant is OK, but a lag that continues to grow over time is an indication you’ll need to give your consumer more resources. 
  • For example, you might need to increase the partition count and hence increase the number of threads consuming from the topic. Or maybe your processing after reading the message is too heavyweight. After consuming a message, you could hand it off to an async queue, where another thread can pick up the message and do the processing.

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