Key Lookup isn’t applied by default?

I’m trying to learn about covering indexes. In the Northwind database, I select from the table Categories:

enter image description here

As you can see the table has a non-clustered index on the column CategoryName.

This SQL query:

select CategoryName  from Categories where Categories.CategoryName like 'Beverages' 

returns an execution plan with an index seek:

enter image description here

However, this:

select CategoryName ,Description from Categories where Categories.CategoryName like 'Beverages' 

returns this execution plan with an index scan using the primary key index, which isn’t expected:

enter image description here

I can find the expected behaviour only when I force the query with the non-clustered index:

 select CategoryName ,Description from Categories     with(index(CategoryName))  where Categories.CategoryName like 'Beverages' 

enter image description here

What is the problem?

Free Reverse Phone Lookup – Is it Worth Your Time and Effort?

There are numerous administrations that guarantee to give a free converse telephone query; do they satisfy the hopes? There’s a tremendous measure of publicizing going on these days for administrations giving a free admittance to the opposite telephone information base, is it worth your time utilizing them? This article investigates the free  consumer phonelist administrations in subtleties and distinguishes its trap and their covered up upsell by which they bring in their cash. 
 
Above all else, what is a free opposite telephone query and what data do they uncover? Administrations, for example, White Pages intensely publicize their free telephone invert search, would they say they are truly exact as they guarantee? Truly and no. Truly, the contact data they give on entering a telephone number is right on the off chance that they have that specific telephone number in their information base and as a rule the telephone number may have enrolled well before. Shouldn’t something be said about numerous unlisted telephone numbers? Indeed, they don’t uncover it. Their data set doesn’t have that data. Additionally after getting to contact data you are given a choice to do a foundation search on the personality uncovered and think about what it accompanies a strong sticker price. In this way the data gave by the free assistance is restricted to numerous quantities of things – little information base, inadequate individual character (only some old location won’t help you), and with an upsell that accompanies a heavy sticker price.
 
It’s smarter to explore and go for an approved outsider help that offers a paid assistance for simply the half of the cost of what these free administrations attempts to upsell you. So settle on a shrewd choice.

Phone Reverse Lookup – Great Tips on How to Reverse Lookup Phone Numbers and Track Do

In this universe of science and innovation, the men of science invest their energy in research facilities looking for something new. We additionally witness their push to manage natural products. Presently this time, it is an iPhone from the place of Apple that has been pulling in all the considerations worldwide in the course of recent months. 
  Buy Mobile Database 
The device irregularities of US can purchase this iPhone right now. Yet, the individuals of Asian nations like India need to hold up to mid 2008 to lay their hands on such an enchantment development. The telephone has joined screen and consolidates the highlights of a cell phone, ipod, advanced coordinator and remote web gadgets. It is a progressive telephone. It does things that no telephone has ever done previously yet it has likewise been said that it needs includes found even on the most essential telephones. So it has welcomed both praise just as analysis. 
 
iPhone is a small, thin, exquisite hand-held PC whose screen is a piece of touch touchy glass. The $500 and $600 models have 4 and 8 GB stockpiling and can store 825 and 1825 tunes individually. The iphone is assemblage of cellphone, video ipod, email terminal, internet browser, camera, morning timer, palm type coordinator and one hell of superficial point of interest. The telephone is so smooth and slender that makes Treos and Blackberrys look large. At the point when the glass of the telephone get smudgy, a sleeve cleans it off yet it doesn’t scratch without any problem. However, the greatest accomplishment in this telephone is the product accessible. It is quick, excellent, menu free and extremely easy to work. The main physical catch underneath the screen consistently opens the landing page showing the symbols for the iphone’s 16 capacities. Records look with a flick of finger; CD fronts flip over as it is flicked. The clients don’t need to check the phone message yet it itself checks the client. The just one catch press uncovers the holding up messages, recorded like email. There is no dialing in, no secret word. To answer a call, the client can tap answer on the screen, or squeeze the minuscule amplifier. iPhone has a speaker telephone and vibration mode however both are powerless. The music or video playback delays until you hang up. In any case, while making a call, be that as it may, the clients need to follow a protracted procedure containing 6 stages: wake the telephone, open its catches, gather the home screen, open the telephone program, see the ongoing calls or speed dial list and select a name. The call quality is simply normal yet email is fabulous. Approaching messages are completely designed, total with illustrations. The clients even can open Word, Excel and PDF reports however can’t alter. The internet browser is extremely commendable. It has different open pages, textual styles, designs, spring up menus, check boxes, interactive connections and dial-capable telephone number. Everything is finished with the tap of a finger.

Data structure for efficient group lookup

I need a data structure, which allows efficient queries for ‘give me the group of x‘.

Let me give you an example:

Group 1: [a, b, c]  Group 2: [d, e] Group 3: [f]  getGroupOf(d) -> [d, e] 

There are no significant constraints on storage or construction time. I only need getGroupOf to be O(logn) or faster.

I am thinking about using a Dictionary<Element, Set<Element>> where entries for all elements in a group share the same set reference. This would make lookup effectively O(1) or O(logn) depending on the dictionary implementation, but would result in a lot of entries.

This feels fairly bloated, and I am wondering: is there is a more elegant data structure to accomplish this?

Turn around Cell Phone Lookup – Technology That Can Fulfill All Of Your Investigative

People grasp the high innovation world that we are venturing now. There are numerous devices that are coming each month on new form programming, similar to mobile phones. PDAs help us in speaking with our family, family members and companions. Individuals may be specific in its highlights however it is pointless thing to talk about. The most significant motivation behind why you are having a PDA is that you have to speak with others by sending messages through content and calling by utilizing your mobile phones. https://www.bcellphonelist.com/armenia-mobile-database/

In fact, having a PDA needs your consideration particularly when somebody messages you and you don’t have a clue who claims that telephone number. You will be irritated and will physically look by asking your family, companions and family members if that number is put away in their telephone directory. It is a serious deal when you don’t have the foggiest idea who possesses it since you may believe that it might be something to cause you hurt. What you don’t know is demonstrated to hurt you. Presumably, you will search for a telephone index and locate that number which is viewed as a hard undertaking. You may mishandle through telephone registries, or different assets, for example, the free venerate PDA queries on the web and come out with nothing.

PostgreSQL efficient lookup for 2 column combinations

I have a PostgreSQL (v. 12) database storing match results. I have integer columns team_home and team_away which have foreign key constraints for team_id in table teams . My question has a few scenarios:

  1. If I want to find all games involving a single team with ID 1 I could do:

SELECT * FROM matches WHERE team_home = 1 OR team_away = 1;

  1. If I wanted to find all games between 2 teams, IDs 1 and 2 I could do:

SELECT * FROM matches WHERE (team_home = 1 AND team_away = 2) OR (team_home = 2 AND team_away = 1);

  1. I want to join my matches table with a teams table:

.

SELECT m.match_id, t1.name, t2.name  FROM matches m  JOIN teams t1 ON t1.team_id = m.team_home  JOIN teams t2 ON t2.team_id = m.team_away  WHERE m.team_home = 1 OR m.team_away = 1; 

The question I have is – are these the optimal queries and can I improve efficiency?

I have read a bit about indexes and this page seems to suggest I could improve my queries across two columns like this by using a GIN index, however that is for text columns and not Foreign Key integer columns.

Alternatively should I create an ARRAY column of team ids and then use an ANY query? (The obvious downside to that is you lose the abilit

Proxy Error, DNS lookup failure for -SOS-

Hello, everyone,

please I need your professional help

I have built a new page (3 months old), and because my page speed was too low, I wanted to perform this. But I made a big mistake! I came across a platform called "Ezoic.com" and followed their instructions and changed my server entries in my DNS provider. And that was the lockdown. My website is no longer accessible, neither on the domain name nor on wp-admin. I don't know what to do anymore. I restored the settings on my server, but…

Proxy Error, DNS lookup failure for -SOS-

Constructing a data structure supporting prioritized key lookup

so this is more or less a shot in the dark as I am feeling stuck. Maybe some of you have an idea which helps.

Here is the problem description (pseudo formal):

I want to have a structure $ T = \{ \hat{x_1}, \hat{x_2}, … \}$ with $ \hat{x_i} = (p_i, k_i, v_{k_i})$ .

$ p_i \in \mathbb{N}$ can be interpreted as an associated priority. They can be considered unqiue.

$ k_i \in \mathcal{K}$ a key index, $ d := |\mathcal{K}|$ is not required to be negligibly small, though generally $ d \lt\lt |T|$

$ v_{k_i} \in \mathcal{V}^{(k_i)}$ a partial key over some universe associated with the given key index. As a little pace killer, this key may not be hashable. The only requirement is totally ordered.

Considering an array $ y = [v_i], i \in \mathcal{K}$ , the structure should be capable of supporting the following operations efficiently:

$ lookup(T, y) \rightarrow \underset{x_i \in T : y[k_i] = v_{k_i}}{arg max}( p_i )$ , i.e. the node $ \hat{x_j}$ with a partial key matching and the highest associated priority.

$ succ(T, y) \rightarrow lookup(T \backslash \{\hat{x_j}\}, y)$ , i.e. the successor (in terms of priority) of a node $ \hat{x_j}$ matching $ y$

Ultimately I would also like efficient insertion and deletion (by priority).

(For insertion: The selection of $ k_i$ for each node is another point of research and can by chosen at the time of insertion. It is essentially possible that this key index is subject to change if it helps the overall structure. But it is also not required that all key indices in $ \mathcal{K}$ are supported for each node, i.e. one might need to insert a node which is only queryable by a single $ k_i$ .)

The key indices are somewhat causing a headache for me. My research so far includes standard priority search trees and dynamic variations thereof. I also found this very interesting, though very theoretical, paper which takes care of the increased dimensionality (kind of) caused by the d-dimensional keys.

I know that I can construct d-dimensional binary search trees with a query complexity of $ O(d + n log(n))$ . These should definitely yield a gain though I am not capable of mapping the priority problem to it (Ref).

But I guess the complexity can be reduced even further if we consider that fact, that each node is only storing partial keys anyway.

My approach so far is somewhat naive as it simply creates a hash map for each key index in $ \mathcal{K}$ and queries each hash map upon lookup. It then aggregates all the results and sorts them by priority. This works fine for hashable keys but a fallback structure has to be used whenever they are not (I am using binary search trees).

How does a TLB lookup compare all keys simultaneously?

I am reading OS Concepts dinosaur book which says, “Each entry in the TLB consists of two parts: a key (or tag) and a value. When the associative memory is presented with an item, the item is compared with all keys simultaneously.”

I checked How does a TLB and data cache work? but it does not say anything about the implementation that allows this parallel checking of the keys.

I read something about a parallel hash table here: http://www.cs.cmu.edu/afs/cs/academic/class/15210-s12/www/lectures/lecture27.pdf

Is this the basic idea? The insertion of a key outputs a frame number and this could either be a hit or miss?