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The Quick and Easy Way to Analyze Numpy Arrays

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The quickest and easiest way to analyze NumPy arrays is by using the numpy.array() method. This method allows you to quickly and easily analyze the values contained in a numpy array. This method can also be used to find the sum, mean, standard deviation, max, min, and other useful analysis of the value contained within a numpy array. Sum You can find the sum of Numpy arrays using the np.sum() function.  For example:  import numpy as np  a = np.array([1,2,3,4,5])  b = np.array([6,7,8,9,10])  result = np.sum([a,b])  print(result)  # Output will be 55 Mean You can find the mean of a Numpy array using the np.mean() function. This function takes in an array as an argument and returns the mean of all the values in the array.  For example, the mean of a Numpy array of [1,2,3,4,5] would be  result = np.mean([1,2,3,4,5])  print(result)  #Output: 3.0 Standard Deviation To find the standard deviation of a Numpy array, you can use the NumPy std() function. This function takes in an array as a par
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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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