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Using SQLite to Examine Data Relationships and Compare Tables

SQLite supplies quite a few methods to view and evaluate knowledge throughout a number of tables. This weblog will focus on SQLite queries that can be utilized to view knowledge relationships:

  • INNER JOIN
  • LEFT JOIN
  • Utilizing A number of Be a part of Operators

And SQLite queries that can be utilized to match tables:

  • INTERSECT
  • UNION
  • UNION ALL
  • EXCEPT



Easy Choose Queries

With a view to illustrate find out how to use SELECT statements, I’ve created a database to maintain monitor of backyard crops and backyard beds, which I seek advice from within the examples I exploit. The database has a crops desk that accommodates data on the totally different backyard crops, together with the plant identify, whether or not the plant requires full solar, and the time of 12 months that the plant begins to bloom. The information within the crops desk could be retrieved with a SELECT question:

SELECT * FROM crops;
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id  identify              full_sun  bloom      
--  ----------------  --------  -----------
1   Bee Balm          0         late spring
2   Petunia           1         summer season     
3   Coneflower        0         summer season     
4   Zinnia            1         late spring
5   Black-Eyed Susan  0         summer season
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Within the full_sun column, the integers 1 and 0 are used to signify the Boolean values of ‘true’ and ‘false’, respectively.

To restrict the result is columns to solely embody the plant’s id quantity and identify, the columns could be specified within the SELECT assertion as a substitute of utilizing *:

SELECT id, identify FROM crops;
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id  identify            
--  ----------------
1   Bee Balm        
2   Petunia         
3   Coneflower      
4   Zinnia          
5   Black-Eyed Susan
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To restrict the question end result to solely these rows that match a sure situation, a WHERE clause could be added to the question. For instance, the next question would solely choose crops that don’t require full daylight:

SELECT * FROM crops WHERE full_sun IS 0;
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id  identify              full_sun  bloom      
--  ----------------  --------  -----------
1   Bee Balm          0         late spring
3   Coneflower        0         summer season     
5   Black-Eyed Susan  0         summer season
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Choose Queries With Be a part of Operators

Retrieving knowledge from a single desk has its makes use of, but it surely doesn’t permit me to simply see the relationships between knowledge on a number of tables. You should utilize be part of statements to view knowledge throughout a number of tables on the identical time.

Our database additionally accommodates a desk with data on backyard beds:



beds

id  gentle        
--  -------------
1   full solar     
2   partial shade
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A kind of plant could be planted in a number of backyard beds, and a backyard mattress can have a number of sorts of crops. To maintain monitor of the relationships between crops and backyard beds, there’s a be part of desk, referred to as plant_beds:



plant_beds

id  plant_id  bed_id
--  --------  ------
1   1         2     
2   4         1     
3   3         2     
4   5         1     
5   1         1
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The connection between the crops, beds, and plant_beds tables could be visualized like this:



INNER JOIN

The INNER JOIN can be utilized to view the crops that correspond to every row within the plant_bed be part of desk. SQLite treats the operators “INNER JOIN”, “JOIN” and “,” precisely the identical, to allow them to be used interchangably.

SELECT plant_beds.id, plant_beds.plant_id, crops.identify, plant_beds.bed_id
FROM plant_beds
INNER JOIN crops
ON plant_beds.plant_id = crops.id
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id  plant_id  identify              bed_id
--  --------  ----------------  ------
1   1         Bee Balm          2     
2   4         Zinnia            1     
3   3         Coneflower        2     
4   5         Black-Eyed Susan  1     
5   1         Bee Balm          1
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Remember to incorporate the ON assertion within the question. The ON operator tells SQLite how the tables relate to one another. With out that instruction, SQLite will return each row from the plant_beds desk matched with each row from the crops database:

SELECT plant_beds.id, plant_beds.plant_id, crops.identify, plant_beds.bed_id
FROM plant_beds
INNER JOIN crops
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id  plant_id  identify              bed_id
--  --------  ----------------  ------
1   1         Bee Balm          2     
1   1         Petunia           2     
1   1         Coneflower        2     
1   1         Zinnia            2     
1   1         Black-Eyed Susan  2     
2   4         Bee Balm          1     
2   4         Petunia           1     
2   4         Coneflower        1     
2   4         Zinnia            1     
2   4         Black-Eyed Susan  1     
3   3         Bee Balm          2     
3   3         Petunia           2     
3   3         Coneflower        2     
3   3         Zinnia            2     
3   3         Black-Eyed Susan  2     
4   5         Bee Balm          1     
4   5         Petunia           1     
4   5         Coneflower        1     
4   5         Zinnia            1     
4   5         Black-Eyed Susan  1     
5   1         Bee Balm          1     
5   1         Petunia           1     
5   1         Coneflower        1     
5   1         Zinnia            1     
5   1         Black-Eyed Susan  1
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This end result consists of Petunias within the response, regardless that they are not presently related to any beds in our plant_beds be part of desk. So regardless that SQLite has returned data from each the crops desk and the plant_beds desk, the response doesn’t signify the connection between the 2 tables.



LEFT JOIN

The reponse to an INNER JOIN question solely consists of the rows from every desk which have a match within the ON assertion. SO, within the instance above, Petunia will not be embody din the response as a result of it’s not included within the plant_beds desk. With a view to see all of the rows from the left desk or the suitable desk, LEFT JOIN or LEFT OUTER JOIN ought to be used as a substitute of INNER JOIN. The response from a LEFT JOIN question will embody the identical rows as an INNER JOIN question, in addition to an additional row from every row within the left-hand desk (or first desk listed within the question) that doesn’t have a mathing row within the right-hand desk (the second desk listed within the question). SQLite makes use of NULL as a default worth for any column that doesn’t have a price within the right-hand desk

SELECT plant_beds.id, plant_beds.plant_id, crops.identify, plant_beds.bed_id
FROM plant_beds
LEFT JOIN crops
ON plant_beds.plant_id = crops.id
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id  plant_id  identify              bed_id
--  --------  ----------------  ------
5   1         Bee Balm          1     
1   1         Bee Balm          2     
              Petunia                 
3   3         Coneflower        2     
2   4         Zinnia            1     
4   5         Black-Eyed Susan  1
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As could be seen on this instance, the LEFT JOIN question end result consists of the Petunia row from the crops desk and makes use of NULL values, which seem as clean areas, for the columns the place there is no such thing as a match for Petunia within the plant_beds desk.



Utilizing a JOIN Assertion With Extra Than Two Tables

INNER JOIN and LEFT JOIN statements could be repeated in a question to provide a end result that features data from a couple of desk. For instance, to see data from the plant_beds desk in addition to particulars from each the crops and beds tables, two INNER JOIN statements can be utilized.

SELECT plant_beds.id, plant_beds.plant_id, crops.identify, plant_beds.bed_id, beds.gentle
FROM plant_beds
INNER JOIN crops
ON plant_beds.plant_id = crops.id
INNER JOIN beds
ON plant_beds.bed_id = beds.id
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id  plant_id  identify              bed_id  gentle        
--  --------  ----------------  ------  -------------
1   1         Bee Balm          2       partial shade
2   4         Zinnia            1       full solar     
3   3         Coneflower        2       partial shade
4   5         Black-Eyed Susan  1       full solar     
5   1         Bee Balm          1       full solar
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Compound Choose Statements

What if, as a substitute of itemizing all crops in a single desk, the crops had been sorted into a number of tables primarily based on traits of every plant. I’ve made three extra database tables to maintain monitor of native crops, crops which can be notably enticing to bees, and crops which can be more likely to entice hummingbirds. After all, there are native crops which can be often known as good decisions for bees and hummingbirds, so the three tables can have some crops in frequent.



native_plants

id  identify                full_sun  bloom      
--  ------------------  --------  -----------
1   Arrowwood Viburnum  0         late spring
2   Bee Balm            0         late spring
3   Black-Eyed Susan    0         summer season     
4   Coneflower          0         summer season     
5   Goldenrod           0         late summer season
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bee_plants

id  identify        full_sun  bloom      
--  ----------  --------  -----------
1   Bee Balm    0         late spring
2   Lavender    1         summer season     
3   Coneflower  0         summer season     
4   Zinnia      1         late spring
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hummingbird_plants

id  identify             full_sun  bloom      
--  ---------------  --------  -----------
1   Petunia          1         summer season     
2   Bee Balm         0         late spring
3   Cardinal Flower  1         mid summer season 
4   Backyard Phlox     0         summer season
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These tables may also be visualized like this:

Representation of multiple plant tables

Now that the crops are organized into a number of tables, it will be good to have the ability to evaluate the tables to one another. This may be finished with compound SELECT statements. Particularly, with the INTERSECT, UNION, UNION ALL, and EXCEPT operators.



INTERSECT

INTERSECT is used to acquire the columns and rows that tables have in frequent.

SELECT identify, bloom FROM native_plants
INTERSECT
SELECT identify, bloom FROM bee_plants
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identify        bloom      
----------  -----------
Bee Balm    late spring
Coneflower  summer season
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To ensure that the INTERSECT question to work, the columns in every SELECT column should match. The SELECT statements will need to have the identical variety of columns, and the columns should return the identical kind of data in order that SQLite can evaluate every column worth.

Word that on this instance, the SELECT assertion will not be utilizing id or * to retrieve the id column from the tables. Whereas the native_plants, bee_plants, and hummingbird_plants tables have some crops in frequent, these crops should not have identical id numbers in every desk. In bee_plants, Bee Balm has an id of 1 and Coneflower has an id of three, whereas in native_plants, Bee Balm has an id 2 and Coneflower has an id of 4. So if the question included the id column, the Bee Balm and Coneflower rows from every desk wouldn’t match, and the INTERSECT operator would return no outcomes.



UNION and UNION ALL

To get the data from a number of tables, no matter whether or not the tables rows are the identical in every desk, use the UNION operator.

SELECT identify, bloom FROM bee_plants
UNION
SELECT identify, bloom FROM hummingbird_plants
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identify             bloom      
---------------  -----------
Bee Balm         late spring
Cardinal Flower  mid summer season 
Coneflower       summer season     
Backyard Phlox     summer season     
Lavender         summer season     
Petunia          summer season     
Zinnia           late spring
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The UNION operator returned the rows from the bee_plants desk and the rows from the hummingbird_plants desk, and it robotically eliminated duplicate rows. With a view to return each row from each tables, even when a row seems in every desk, the UNION ALL operator can be utilized.

SELECT identify, bloom FROM bee_plants
UNION ALL
SELECT identify, bloom FROM hummingbird_plants
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identify             bloom      
---------------  -----------
Bee Balm         late spring
Lavender         summer season     
Coneflower       summer season     
Zinnia           late spring
Petunia          summer season     
Bee Balm         late spring
Cardinal Flower  mid summer season 
Backyard Phlox     summer season
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Bee Balm seems twice within the end result from the UNION ALL question as a result of it exists in each the hummingbird_plants desk and the bee_plants desk.



EXCEPT

The EXCEPT operator can be utilized to retrieve rows from one desk that don’t seem in one other desk.

SELECT identify, bloom FROM native_plants
EXCEPT
SELECT identify, bloom FROM bee_plants
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identify                bloom      
------------------  -----------
Arrowwood Viburnum  late spring
Black-Eyed Susan    summer season     
Goldenrod           late summer season
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Conclusion

Detailed documentation of SQLite’s SELECT statements, together with the operators mentioned above and lots of different choices for establishing SELECT assertion, could be discovered on SQLite’s web site : https://sqlite.org/lang_select.html

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