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Step-by-Step Guide to Reading Different Files in Python

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 In the world of data science, automation, and general programming, working with files is unavoidable. Whether you’re dealing with CSV reports, JSON APIs, Excel sheets, or text logs, Python provides rich and easy-to-use libraries for reading different file formats. In this guide, we’ll explore how to read different files in Python , with code examples and best practices. 1. Reading Text Files ( .txt ) Text files are the simplest form of files. Python’s built-in open() function handles them effortlessly. Example: # Open and read a text file with open ( "sample.txt" , "r" ) as file: content = file.read() print (content) Explanation: "r" mode means read . with open() automatically closes the file when done. Best Practice: Always use with to handle files to avoid memory leaks. 2. Reading CSV Files ( .csv ) CSV files are widely used for storing tabular data. Python has a built-in csv module and a powerful pandas library. Using cs...
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10 Tricky Apache-Storm Interview Questions

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The storm is a real-time computation system. It is a flagship software from Apache foundation. Has the capability to process in-stream data. You can integrate traditional databases easily in the Storm. The tricky and highly useful interview questions given in this post for your quick reference. Bench mark for Storm is a million tuples processed per second per node.

Interview Questions

Tricky Interview Questions

1) Real uses of Storm?

A) You can use in real-time analytics, online machine learning, continuous computation, distributed RPC, ETL

2) What are different available layers on Storm?
  • Flux
  • SQL
  • Streams API
  • Trident 
3)  The real use of SQL API on top of Storm?

A) You can run SQL queries on stream data

4) Most popular integrations to Storm?
  1. HDFS
  2. Cassandra
  3. JDBC
  4. HIVE
  5. HBase
5) What are different possible Containers integration with Storm?
  1. YARN
  2. DOCKER
  3. MESOS
6) What is Local Mode?

A) Running topologies in the Local server we can say as Local Mode.

7) Where all the Events Stored in Storm?
A) Event Logger mechanism saves all events

8) What are Serializable data types in Storm?
A) Storm can serialize primitive types, strings, byte arrays, ArrayList, HashMap, and HashSet

9) What are Hooks in Storm?
A) You can place the custom code in Storm and you can run events many times

10) What is the Joining of Streams?
A) Streams from different sources you can Join on a particular join condition

References

Apache Spark Vs Apache Storm Vs Tableau

  • The storm is super past in stream processing engine for Big data analytics
  • Tableau is Data warehousing presentation tool
  • Spark is Cluster Maintenance and Fault Tolerance
Apache storm

  References

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