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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 ...
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HBASE: Top Features in Storing Big data

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In this post explained top features added in HBase to handle the data. The Java implementation of Google's Big Table you can call it as HBASE.  In HBase, the data store as two parts.
hadoop hbase

Row Key : 00001 
Column : (Column Qualifier:Version:Value)

Features of HBASE

  • HBase data stores consist of one or more tables, which are indexed by row keys.
  • Data is stored in rows with columns, and rows can have multiple versions.
  • By default, data versioning for rows is implemented with time stamps.
  • Columns are grouped into column families, which must be defined upfront during table creation. Column families are stored together on disk, which is why HBase is referred to as a column-oriented datastore
New features of HBASE check now

In addition...

HBase is a distributed data store, which leverages a network-attached cluster of low-cost commodity servers to store and persist data.HBase architecture is a little trick to know.

Region Servers...

RegionServers are the software processes (often called daemons) you activate to store and retrieve data in HBase.

The big difference...

  • HABSE handles growing data or big data. HBase automatically scales as you add data to the system. A huge benefit compared to most database management systems, which require manual intervention to scale the overall system beyond a single server. 
  • With HBase, as long as you have in the rack another spare server that's configured, scaling is automatic.

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