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Declaring a default constraint when creating a table
I am creating a new table in Microsoft SQL server 2000 by writing the code instead of using the GUI, I am trying to learn how to do it "the manual way".
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UITableView - scroll to the top
In my table view I have to scroll to the top. But I cannot guarantee that the first object is going to be section 0, row 0. May be that my table view will start from section number 5.
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access denied for load data infile in MySQL
...mple, this gives the permission problem:
LOAD DATA INFILE '{$file}' INTO TABLE {$table}
Add LOCAL to your statement and the permissions issue should go away. Like so:
LOAD DATA LOCAL INFILE '{$file}' INTO TABLE {$table}
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MySql : Grant read only options?
...ns on database.
It depends on how you define "all read."
"Reading" from tables and views is the SELECT privilege. If that's what you mean by "all read" then yes:
GRANT SELECT ON *.* TO 'username'@'host_or_wildcard' IDENTIFIED BY 'password';
However, it sounds like you mean an ability to "see" ...
How to insert a SQLite record with a datetime set to 'now' in Android application?
Say, we have a table created as:
10 Answers
10
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Why would anyone use set instead of unordered_set?
... and many other places. What I understand is that unordered_set is hash table with O(1) lookup complexity. On the other hand, set is nothing but a tree with log(n) lookup complexity. Why on earth would anyone use set instead of unordered_set? i.e is there a need for set anymore?
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Generate a random number in the range 1 - 10
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Actually I don't know you want to this.
try this
INSERT INTO my_table (my_column)
SELECT
(random() * 10) + 1
;
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MySQL string replace
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UPDATE your_table
SET your_field = REPLACE(your_field, 'articles/updates/', 'articles/news/')
WHERE your_field LIKE '%articles/updates/%'
Now rows that were like
http://www.example.com/articles/updates/43
will be
http://www.examp...
SQL to find the number of distinct values in a column
...aggregate function:
SELECT COUNT(DISTINCT column_name) AS some_alias FROM table_name
This will count only the distinct values for that column.
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Compare two DataFrames and output their differences side-by-side
... False "On vacation" """)
df1 = pd.read_table(DF1, sep='\s+', index_col='id')
df2 = pd.read_table(DF2, sep='\s+', index_col='id')
diff_pd(df1, df2)
Output:
from to
id col
112 score 1.11 1.21
113 ...