I have database with game square (called game):
id | x | y | isGold
I program I have array of coords like this:
var test = [
{x:1, y:2},
{x:2, y:4}
]
I want select all rows from game table somethink like this:
Select * from game where x and y in (?) where isGold = true, [test] ...
But problem is, that I don't know how to create select with object. I can transform my array to anything, how can I make a query for this problem?
If you use mysqljs/mysql npm package try this:
Select * from game where (x, y) IN (?) where isGold = true, [[[1, 2], [2, 4]]
Look at the doc
https://github.com/mysqljs/mysql#performing-queries
Arrays are turned into list, e.g. ['a', 'b'] turns into 'a', 'b'
Nested arrays are turned into grouped lists (for bulk inserts), e.g.
[['a', 'b'], ['c', 'd']] turns into ('a', 'b'), ('c', 'd')
Related
Suppose that I have a MySQL table with a JSON field that contains only numbers, like this (note: using MySQL 8):
CREATE TABLE my_table (
id int,
some_field json
);
Sample data:
id: 1
some_field: [1, 2, 3, 4, 5]
id: 2
some_field: [3, 6, 7]
id: 3
some_field: null
I would like to merge another array of data with the existing values of some_field, while removing duplicates. I was hoping that this might work, but it didn't:
update my_table set some_field = JSON_MERGE([1, 2, 3], some_field)
The result of this would be:
id: 1
some_field: [1, 2, 3, 4, 5]
id: 2
some_field: [1, 2, 3, 6, 7]
id: 3
some_field: [1, 2, 3]
Considering you have 3 records in your table and you want to merge 1 and 2 as mentioned in your example.
I hope JavaScript is suitable to follow through for you.
// Get both the records
const records = db.execute(“SELECT id, some_field FROM my_table WHERE id=1 OR id=2”);
// You get both the rows.
// Merging row1, you can either use the Set data structure if you’re dealing with numbers like your example, or you could loop using a map and use the spread operator if using JSON. Since your object is an array, I’ll just be explaining to merge 2 arrays.
records[0].some_field = Array.from(new Set(records[0].some_field + record[1].some_field))
// Same for second record.
records[1].some_field = Array.from(new Set(records[0].some_field + record[1].some_field))
// Now update both the records in the database one by one.
I have a table which has a JSON type field where I save a number array like [1, 2, 3, 4].
I want to select records in which its array set contains at least one element of another array I have in a php script.
I know that the JSON_CONTAINS function can be used to see if my array contains an element, but how can I select if both arrays has at least a common number (no matter in what index).
For example:
[1, 2, 3] and [5, 0, 2] -> True
[9, 2, 1] and [0, 5, 3] -> False
[4, 0, 2] and [4, 2, 6] -> True
Currently, Im using multiple JSON_CONTAINS to check if there are common elements, this way:
SELECT *
FROM mytable
WHERE JSON_CONTAINS(ar, 0, '$') OR
JSON_CONTAINS(ar, 1, '$') OR
JSON_CONTAINS(ar, 2, '$')
But I guess there may be a more elegant way of doing this.
I searched but couldn't find the appropiate function, but if this is a dupe, let me know.
Thanks in advance!
https://dev.mysql.com/doc/refman/8.0/en/json-search-functions.html#function_json-overlaps
mysql> SELECT JSON_OVERLAPS("[1,3,5,7]", "[2,5,7]");
+---------------------------------------+
| JSON_OVERLAPS("[1,3,5,7]", "[2,5,7]") |
+---------------------------------------+
| 1 |
+---------------------------------------+
my test code:
local jsonc = require "jsonc"
local x = {
a = 1,
b = 2,
c = 3,
d = 4,
e = 5,
}
for k, v in pairs(x) do
print(k,v)
end
print(jsonc.stringify(x))
output:
a 1
c 3
b 2
e 5
d 4
{"a":1,"c":3,"b":2,"e":5,"d":4}
someone help:
from for pairs output, lua store table by key hash order, how can i change it?
i need output: {"a":1,"b":2,"c":3,"d":4,"e":5}
thanks
Lua tables can't preserve the order of their keys. There are two possible solutions.
You can store the keys in a separate array and iterate through that whenever you need to iterate through the table:
local keys = {'a', 'b', 'c', 'd', 'e'}
Or, instead of a hash table, you can use an array of pairs:
local x = {
{'a', 1},
{'b', 2},
{'c', 3},
{'d', 4},
{'e', 5},
}
i have array like this: [1, 1, 1, 2, 3]. How i can get users with a duplicate? For example this query return list without duplicate
list= User.objects.filter(id__in=[1, 1, 1, 2, 3])
for example it will be users with id's:
1,
2,
3
but i need list of users like this:
1,
1,
1,
2,
3
list = []
for x in [1, 1, 1, 2, 3]:
list.append(User.objects.filter(id=x)
It this what you mean? I don't quite understand the spacing.
Get your queryset sorted in the right order. .order_by('id) for ascending by id (which may be the default anyway). Then iterate over the queryset with code to make extra operations with the same object (or a copy thereof) as dictated by the list of IDs.
idlist = [1, 1, 1, 2, 3]
queryset = User.objects.filter(id__in = idlist ).order_by('id')
for object in queryset:
for _ in range( idlist.count( object.id))
do_something_with( object)
Note, this is only one DB call (one queryset), unlike the accepted answer which does one DB query for each element in the id list. Not good.
I have a dataframe and I am trying to turn the column into a comma separated list. The end goal is to pass this comma seperated list as a list of filtered items in a SQL query.
How do I go about doing this?
> import pandas as pd
>
> mydata = [{'id' : 'jack', 'b': 87, 'c': 1000},
> {'id' : 'jill', 'b': 55, 'c':2000}, {'id' : 'july', 'b': 5555, 'c':22000}]
df = pd.DataFrame(mydata)
df
Expected solution - note the quotes around the ids since they are strings and the items in column titled 'b' since that is a numerical field and the way in which SQL works. I would then eventually send a query like
select * from mytable where ids in (my_ids) or values in (my_values):
my_ids = 'jack', 'jill','july'
my_values = 87,55,5555
I encountered a similar issue and solved it in one line using values and tolist() as
df['col_name'].values.tolist()
So in your case, it will be
my_ids = my_data['id'].values.tolist() # ['jack', 'jill', 'july']
my_values = my_data['b'].values.tolist()
Let's use apply with argument 'reduce=False' then check the dtype of the series and apply the proper argument to join:
df.apply(lambda x: ', '.join(x.astype(str)) if x.dtype=='int64' else ', '.join("\'"+x.astype(str)+"\'"), reduce=False)
Output:
b 87, 55, 5555
c 1000, 2000, 22000
id 'jack', 'jill', 'july'
dtype: object