create table tmp as select code,avg(how-low)/low as vol from quote group by code;
select avg(vol) from tmp
I create a new table with the first statement ,then select ave(vol) from tmp table.How can i combine the two sqlite statements into one statement?
If you do not need the temporary table later, use a common table expression:
WITH tmp AS (SELECT avg(how-low)/low AS vol
FROM quote
GROUP BY code)
SELECT avg(vol)
FROM tmp
If you have an outdated SQLite version (older than 3.8.3), you could use a subquery instead:
SELECT avg(vol)
FROM (SELECT avg(how-low)/low AS vol
FROM quote
GROUP BY code)
Related
Background
I am using R Studio to connect R to Microsoft SQL Sever Management Studio. I am reading tables into R as follows:
library(sqldf)
library(DBI)
library(odbc)
library(data.table)
TableX <- dbGetQuery(con, statement = "SELECT * FROM [dim1].[dimA].[TableX]")
Which for some tables works fine. However for most tables which have a binary ID variable
the following happens:
TableA <- dbGetQuery(con, statement = "SELECT * FROM [dim1].[dimA].[TableA]")
Error in result_fetch(res#ptr, n) :
nanodbc/nanodbc.cpp:xxx: xxxxx: [Microsoft][ODBC SQL Server Driver]Invalid Descriptor Index
Warning message:
In dbClearResult(rs) : Result already cleared
I figured out that the problem is caused by the first column, which I can select like this:
TableA <- dbGetQuery(con, statement = "SELECT ID FROM [dim1].[dimA].[TableA]")
and looks as follows:
AlwaysLearning mentioned in the comments that this is a recurring problem (1, 2, 3). The query only works when ID is selected last:
TableA <- dbGetQuery(con, statement = "SELECT AEE, ID FROM [dim1].[dimA].[TableA]")
Updated Question
The question is essentially how I can read in the table with the ID variable last, without specifying all table variables each time (because this would be unworkable).
Possible Workaround
I thought a work around could be to select ID as an integer:
TableA <- dbGetQuery(con, statement = "SELECT CAST(ID AS int), COL2 FROM [dim1].[dimA].[TableA]")
However how do I select the whole table in this case?
I am an SQL beginner, but I thought I could solve it by using something like this (from this link):
TableA <- dbGetQuery(con, statement = "SELECT * EXCEPT(ID), SELECT CAST(ID AS int) FROM [[dim1].[dimA].[TableA]")
Where I select everything but the ID column, and then the ID column last. However the solution I suggest is not accepted syntax.
Other links
A similar problem for java can be found here.
I believe I have found a workaround that meets your requirements using a table alias.
By assigning the alias T to the table I want to query, it allows me to select both a specific column ([ID]) as well as all columns in the aliased table without the need to explicitly specify them all by name.
This returns all columns of the table (including the ID column) as well as a copy of the ID column at the end of the table.
I then remove the ID column from the resulting table.
This leaves you with the desired result: all columns of a table in the order that they appear with the exception of the ID column that is placed at the end.
PS: For the sake of completeness, I have provided a template of my own DBIConnection object. You can substitute this with the specifics of your own DBIConnection object.
library(sqldf)
library(DBI)
library(odbc)
library(data.table)
con <- dbConnect(odbc::odbc(),
.connection_string = 'driver={YourDriver};
server=YourServer;
database=YourDatabase;
Trusted_Connection=yes'
)
dataframe <- dbGetQuery(con, statement= 'SELECT T.*, T.[ID] FROM [SCHEMA_NAME].[TABLE_NAME] AS T')
dataframe_scoped <- dataframe[,-1]
I have a database A.db, which contains tables t1, t2 and t3.
Now I want to create a new database B.db, which contains t1 and some chosen columns col1 and col4 from t2.
With .import I get hundreds of errors and it seems to work only for full tables.
.output sounds like I just save the output as it would be printed.
Basically, I need an insert into foo select ... across different files. How can I do this?
First you must attach A.db to your current database and give it an alias like adb.
Then write the insert statement just like you would if all the tables existed in the same database, qualifying the column names with the database alias.
It's a good practice to include in the insert into... statement inside parentheses all the column names of the table foo for which you will set values from the other 2 tables, but also be sure that the order of the columns is the same with the order of the columns in the select list:
attach database 'pathtoAdatabase/A.db' as adb;
insert into foo (column1, column2, .......)
select adb.t1.column1, adb.t1.column2, ...., adb.t2.col1, adb.t2.col4
from adb.t1 inner join adb.t2
on <join condition>
Replace <join condition> with the conditions on whichyou will join the 2 tables to makes the rows that you will insert into foo, something like:
adb.t1.id = adb.t2.id
I have a SQLite table where one column contains a JSON array containing 0 or more values. Something like this:
id|values
0 |[1,2,3]
1 |[]
2 |[2,3,4]
3 |[2]
What I want to do is "unfold" this into a list of all distinct values contained within the arrays of that column.
To start, I am using the JSON1 extension's json_each function to extract a table of values from a row:
SELECT
value
FROM
json_each(
(
SELECT
values
FROM
my_table
WHERE
id == 2
)
)
Where I can vary the id (2, above) to select any row in the table.
Now, I am trying to wrap this in a recursive CTE so that I can apply it to each row across the entire table and union the results. As a first step I replicated (roughly) the results from above as follows:
WITH RECURSIVE result AS (
SELECT null
UNION ALL
SELECT
value
FROM
json_each(
(
SELECT
values
FROM
my_table
WHERE
id == 2
)
)
)
SELECT * FROM result;
As the next step I had originally planned to make id a variable and increment it (in a similar manner to the first example in the documentation, but haven't been able to get that to work.
I have gone through the other examples in the documentation, but they are somewhat more complex and I haven't been able to distill those down to see how they might apply to this problem.
Can someone provide a simple example of how to solve this (or a similar problem) with a recursive CTE?
Of course, my goal is to solve the problem with or without CTEs so Im also happy to hear if there is a better way...
You do not need a recursive CTE for this.
To call json_each for multiple source rows, use a join:
SELECT t1.id, t2.value
FROM my_table AS t1
JOIN json_each((SELECT "values" FROM my_table WHERE id = t1.id)) AS t2;
I'm working on a database to keep track of packages I need for a personal project. I am also treating this as an exercise to teach myself database design and SQL. The database I am using has a schema like the following:
CREATE TABLE packages
(
ID INTEGER PRIMARY KEY,
Name TEXT UNIQUE ON CONFLICT REPLACE NOT NULL ON CONFLICT IGNORE
);
CREATE TABLE dependencies
(
dependentPackage INTEGER REFERENCES pages(ID),
requiredPackage INTEGER REFERENCES pages(ID)
);
where the package referenced by dependencies.dependentPackage depends on the package referenced by dependencies.requiredPackage
I want a query with a column NumPackagesRequired, which returns a table that looks something like this:
packageName | NumDependencies
package1 | 6
package5 | 8
package9 | 1
I cannot achieve this by trying:
SELECT p.name AS packageName, count (d.requiredPackage) AS numDependencies
FROM packages p
JOIN dependencies d ON d.dependentPackage=p.ID;
because it returns only one row, containing the first package's name and the count of all the requirements.
I tried nesting a SELECT statement as a parameter to the count() function, but I still only got a single row of results. I have searched the sqlite documentation with no degree of luck.
How can I get a table like the one expected above?
When you are using GROUP BY, aggregate functions are computed over each group:
SELECT p.name AS packageName,
count (d.requiredPackage) AS numDependencies
FROM packages p
JOIN dependencies d ON d.dependentPackage=p.ID
GROUP BY p.name;
Alternatively, move the couting into a correlated subquery:
SELECT name AS packageName,
(SELECT count(*)
FROM dependencies
WHERE dependentPackage = packages.ID
) AS numDependencies
FROM packages;
I want to make a volatile table using teradata.
In the select statement I am using multiple columns from different tables.
However, some of the columns in the different tables have same names.
Therefore, I am getting a 'duplication column error'.
The question is - is there any workaround to bypass this error?
Is it possible to add for example table name to column name?
This is how my code looks:
CREATE MULTISET VOLATILE TABLE test
AS (
SEL *
FROM Table_A Left JOIN Table_B
...
)
WITH DATA
ON COMMIT PRESERVE ROWS
Instead of doing a select * , select individual column names and put aliases next to it. This will bypass the error.
A select all statement only works if you're working off one table. If you're retrieving all data from multiple tables, you've to specify that in your select statement.
CREATE MULTISET VOLATILE TABLE test AS
(
SELECT Table_A.*
, Table_B.*
FROM Table_A
LEFT JOIN Table_B ON ...
...
)
WITH DATA PRIMARY INDEX(«PI»)
ON COMMIT PRESERVE ROWS