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15 Python Tips : How to Write Code Effectively

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 Here are some Python tips to keep in mind that will help you write clean, efficient, and bug-free code.     Python Tips for Effective Coding 1. Code Readability and PEP 8  Always aim for clean and readable code by following PEP 8 guidelines.  Use meaningful variable names, avoid excessively long lines (stick to 79 characters), and organize imports properly. 2. Use List Comprehensions List comprehensions are concise and often faster than regular for-loops. Example: squares = [x**2 for x in range(10)] instead of creating an empty list and appending each square value. 3. Take Advantage of Python’s Built-in Libraries  Libraries like itertools, collections, math, and datetime provide powerful functions and data structures that can simplify your code.   For example, collections.Counter can quickly count elements in a list, and itertools.chain can flatten nested lists. 4. Use enumerate Instead of Range     When you need both the index and the value in a loop, enumerate is a more Pyth

5 HBase Vs. RDBMS Top Functional Differences

Here're the differences between RDBMS and HBase. HBase in the Big data context has a lot of benefits over RDBMS. The listed differences below make it understandable why HBASE is popular in Hadoop (or Bigdata) platform.

5 HBase Vs. RDBMS Top Functional Differences

5 HBase Vs. RDBMS Top Functional Differences


Here're the differences unlock now.

Random Accessing


HBase handles a large amount of data that is store in a distributed manner in the column-oriented format while RDBMS is systematic storage of a database that cannot support a random manner for accessing the database.

Database Rules


RDBMS strictly follows Codd's 12 rules with fixed schemas and row-oriented manner of database and also follows ACID properties.


HBase follows BASE properties and implements complex queries.
Secondary indexes, complex inner and outer joins, count, sum, sort, group, and data of page and table can easily be accessible by RDBMS.

Storage


From small to medium storage application there is the use of RDBMS that provides the solution with MySQL and PostgreSQL whose size increase with concurrency and performance. 


Codd's rules always need to keep in mind while extending the size of the database in the use of data processing.

Data Integrity


RDBMS focuses on and emphasizes consistency, referential integrity, abstraction from the physical layer, and complex queries through SQL language.

Takeaway

  • There is no single-point failure in HBASE. You always have backup data.
  • The server regions have the flexibility to share or rebalance the load among the servers.
  • Automatic partition helps to distribute its workload among servers. It happens with its in-built feature of HBASE.
  • The cost involved in the maintenance of HBASE is comparatively low.


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