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How does database indexing work?

By : Ian Thake
Date : July 26 2020, 05:00 PM
this will help Why is it needed?
When data is stored on disk-based storage devices, it is stored as blocks of data. These blocks are accessed in their entirety, making them the atomic disk access operation. Disk blocks are structured in much the same way as linked lists; both contain a section for data, a pointer to the location of the next node (or block), and both need not be stored contiguously.
code :
Field name       Data type      Size on disk
id (Primary key) Unsigned INT   4 bytes
firstName        Char(50)       50 bytes
lastName         Char(50)       50 bytes
emailAddress     Char(100)      100 bytes
Field name       Data type      Size on disk
firstName        Char(50)       50 bytes
(record pointer) Special        4 bytes

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How important is indexing and clustered indexing to database performance?

By : brenjp
Date : March 29 2020, 07:55 AM
like below fixes the issue Very veryA(G,G) important. In my opinion, wise indexing is the absolute most important thing in DB performance optimization.
This is not an easy topic to cover in a single answer. Good indexing requires knowledge of queries going to happen on the database, making a large number of trade-offs and understanding the implication of a specific index in the specific DB engine. But it's very important nevertheless.

Work with a row in a pandas dataframe without incurring chain indexing (not coping just indexing)

By : krunal
Date : March 29 2020, 07:55 AM
hop of those help? My data is organized in a dataframe: , This should work:
code :
row_of_interest = df.loc['R2', :]
row_of_interest.is_copy = False
row_of_interest['Col2'] = row_of_interest['Col2'] + 1000
import pandas as pd
import numpy as np

data = {'Col1' : [4,5,6,7], 'Col2' : [10,20,30,40], 'Col3' : [100,50,-30,-50], 'Col4' : ['AAA', 'BBB', 'AAA', 'CCC']}

df = pd.DataFrame(data=data, index = ['R1','R2','R3','R4'])

row_of_interest         = df.loc['R2']
row_of_interest.is_copy = False
new_cell_value          = row_of_interest['Col2'] + 1000
row_of_interest['Col2'] = new_cell_value

print row_of_interest 

df.loc['R2'] = row_of_interest 

print df
    Col1  Col2  Col3 Col4
R1     4    10   100  AAA
R2     5  1020    50  BBB
R3     6    30   -30  AAA
R4     7    40   -50  CCC

Database indexing - what is the purpose of indexing primary keys

By : Mohsen Talebi
Date : March 29 2020, 07:55 AM
I hope this helps . The primary key is an index -- keys are indexes! It's just a special name for a special kind of index which is always unique, and which may have an automatically assigned value.
In some databases, the rows are sometimes (or always) stored in the same order as the primary key. In these situations, the primary key may not need to be separately indexed -- the order of the rows is enough of an index on its own.

Django: JSONField + Full Text Search + Indexing -> Seq Scan. How to configure indexing to work?

By : DanielS
Date : March 29 2020, 07:55 AM
will help you Based on this article I found short solution for Django 2.2+
code :
from django.contrib.postgres.fields import JSONField
from django.contrib.postgres.indexes import GinIndex
from django.contrib.postgres.search import SearchVectorField, SearchVector
from django.db import models

class ProfileUser(models.Model):
    name = JSONField()
    search_vector = SearchVectorField(null=True)

    class Meta:
        indexes = [GinIndex(fields=["search_vector"], name="user_full_name_gin_idx")]

    def save(self, *args, **kwargs):
        super(ProfileUser, self).save(*args, **kwargs)
from django.contrib.postgres.search import SearchQuery
from apps.profiles.models import ProfileUser

ProfileUser.objects.create(name=[{'name': 'Adriano Celentano', 'lang': 'en'}])

partial_name = 'celen'  # or 'celentano adr'

query = re.sub(r'[!\'()|&]', ' ', partial_name).strip()
if query:
    query = re.sub(r'\s+', ' & ', query)
    query += ':*'  # -> 'celen:*' or 'celentano & adr:*'

    # Please note, that `search_type` parameter was added to Django 2.2.
    ProfileUser.objects.filter(search_vector=SearchQuery(query, search_type='raw')).explain()

Database indexing - how does it work?

By : user3882228
Date : March 29 2020, 07:55 AM
like below fixes the issue Database products (RDMS) such as Oracle, MySQL builds their own indexing system, they give some control to the database administrators however nobody exactly knows what happens on the background except people makes research in that area, so why indexing :
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