I am using snowflake as a data warehouse. I have a CSV file at AWS S3. I am writing a merge sql to merge data received in CSV to the table in snowflake. I have a column in time dimension table with data type as Number(38,0) data type in SF. This table holds all dates time, one e.g. is of column
time_id= 232 and time=12:00
In CSV I am getting a column with the label as time and value as 12:00.
In merge sql I am fetching this value and trying to get time_id for it.
update table_name set start_time_dim_id = (select time_id from time_dim t where t.time_name = csv_data.start_time_dim_id)
On this statement I am getting this error "SQL compilation error: Unsupported subquery type cannot be evaluated"
I am struggling to solve it, during this I google for it and got one reference for it
https://github.com/snowflakedb/snowflake-connector-python/issues/251
So want to make sure if anyone have encountered this issue? If yes, will appreciate pointers over it.
It seems like a conversion issue. I suggest you to check the data in CSV file. Maybe there is a wrong or missing value. Please check your data, and make sure it returns numeric values
create table simpleone ( id number );
insert into simpleone values ( True );
The last statement fails with:
SQL compilation error: Expression type does not match column data type, expecting NUMBER(38,0) but got BOOLEAN for column ID
If you provide sample data, and SQL to produce this error, maybe we can provide a solution.
unfortunately correlated and nested subqueries in Snowflake are a bit limited at this stage.
I would try running something like this:
update table_name
set start_time_dim_id= time_id
from time_dim
where t.time_name=csv_data.start_time_dim_id
Related
I'm trying to extract data from a bytea column which stores JSON data in Postgres 11.9 version.
However, the my code is throwing an error:
ERROR: invalid input syntax for type json
DETAIL: Token "" is invalid.
CONTEXT: JSON data, line 1: ...
Here is the sample data:
create table EMPLOYEE (PAYMENT bytea,NAME character varying);
insert into EMPLOYEE
values ('[{"totalCode":{"code":"EMPLOYER_TAXES"},"totalValue":{"amount":122.5,"currencyCode":"USD"}},{"totalCode":{"code":"OTHER_PAYMENTS"},"totalValue":{"amount":0.0,"currencyCode":"USD"}},{"totalCode":{"code":"GROSS_PAY"},"totalValue":{"amount":1000.0,"currencyCode":"USD"}},{"totalCode":{"code":"TOTAL_HOURS"},"totalValue":{"amount":40.0}}]'::bytea,'Tom')
;
Here is my query:
SELECT *
FROM EMPLOYEE left outer join lateral
jsonb_array_elements(PAYMENT::text::jsonb) element1 on true ;
Please help me in accessing data from this array. Data is always JSON in format.
There was a restriction to use bytea for this column.
You are making your life unnecessary hard by storing JSON values in a bytea column. Just because this is the recommended way in Oracle, doesn't mean this is a good choice for Postgres.
The correct solution is to change that column to jsonb. You will have to have a DBMS specific layer in your application anyway as the actual functions and operators you are using are very different.
Having said that, you can get away with this awful choice by using the convert_from() method:
select e.name, element1.*
from employee e
left join lateral jsonb_array_elements(convert_from(PAYMENT, 'UTF-8')::jsonb) element1 on true;
I also think you should change your INSERT statement to do an explicit conversion from text to bytea so that you can be sure the correct encoding is used:
insert into employee (payment, name)
values (convert_to('[{...}]', 'UTF-8'),'Tom');
But again: the only correct solution is to change that column to jsonb (or least json)
I'm using a PostgreSQL with a Go driver. Sometimes I need to query not existing fields, just to check - maybe something exists in a DB. Before querying I can't tell whether that field exists. Example:
where size=10 or length=10
By default I get an error column "length" does not exist, however, the size column could exist and I could get some results.
Is it possible to handle such cases to return what is possible?
EDIT:
Yes, I could get all the existing columns first. But the initial queries can be rather complex and not created by me directly, I can only modify them.
That means the query can be simple like the previous example and can be much more complex like this:
WHERE size=10 OR (length=10 AND n='example') OR (c BETWEEN 1 and 5 AND p='Mars')
If missing columns are length and c - does that mean I have to parse the SQL, split it by OR (or other operators), check every part of the query, then remove any part with missing columns - and in the end to generate a new SQL query?
Any easier way?
I would try to check within information schema first
"select column_name from INFORMATION_SCHEMA.COLUMNS where table_name ='table_name';"
And then based on result do query
Why don't you get a list of columns that are in the table first? Like this
select column_name
from information_schema.columns
where table_name = 'table_name' and (column_name = 'size' or column_name = 'length');
The result will be the columns that exist.
There is no way to do what you want, except for constructing an SQL string from the list of available columns, which can be got by querying information_schema.columns.
SQL statements are parsed before they are executed, and there is no conditional compilation or no short-circuiting, so you get an error if a non-existing column is referenced.
A user can only modify the ST_ASSMT_NM and , CAN_DT columns in the ST_ASSMT_REF record. In our system, we keep history in the same table and we never really update a record, we just insert a new row to represent the updated record. As a result, the "active" record is the record with the greatest LAST_TS timestamp value for a VENDR_ID. To prevent the possibility of an update to columns that cannot be changed, I wrote the logical UPDATE so that it retrieves the non-changable values from the original record and copies them to the new one being created. For the fields that can be modified, I pass them as params,
INSERT INTO GSAS.ST_ASSMT_REF
(
VENDR_ID
,ST_ASSMT_NM
,ST_CD
,EFF_DT
,CAN_DT
,LAST_TS
,LAST_OPER_ID
)
SELECT
ORIG_ST_ASSMT_REF.VENDR_ID
,#ST_ASSMT_NM
,ORIG_ST_ASSMT_REF.ST_CD
,ORIG_ST_ASSMT_REF.EFF_DT
,#CAN_DT
,CURRENT TIMESTAMP
,#LAST_OPER_ID
FROM
(
SELECT
ST_ASSMT_REF_ACTIVE_V.VENDR_ID
,ST_ASSMT_REF_ACTIVE_V.ST_ASSMT_NM
,ST_ASSMT_REF_ACTIVE_V.ST_CD
,ST_ASSMT_REF_ACTIVE_V.EFF_DT
,ST_ASSMT_REF_ACTIVE_V.CAN_DT
,CURRENT TIMESTAMP
,ST_ASSMT_REF_ACTIVE_V.LAST_OPER_ID
FROM
G2YF.ST_ASSMT_REF_ACTIVE_V ST_ASSMT_REF_ACTIVE_V --The view of only the most recent, active records
WHERE
ST_ASSMT_REF_ACTIVE_V.VENDR_ID = #VENDR_ID
) ORIG_ST_ASSMT_REF;
However, I am getting this error:
DB2 SP
:
ERROR [42610] [IBM][DB2] SQL0418N The statement was not processed because the statement contains an invalid use of one of the following: an untyped parameter marker, the DEFAULT keyword, or a null value.
It appears as though DB2 will not allow me to use a variable in a SELECT statement. For example, when I do this in TOAD for DB2:
select 1, #vendorId from SYSIBM.SYSDUMMY1
I get a popup dialog box. When I provide any string value, I get the same error.
I usually use SQL Server and I'm pretty sure I wouldn't have an issue doing this but I am not sure how to handle it get.
Suggestions? I know that I could do this in two seperate commands, 1 query SELECT to retreive the original VALUES and then supply the returned values and the modified ones to the INSERT command, but I should be able to do thios in one. Why can't I?
As you mentioned in your comment, DB2 is really picky about data types, and it wants you to cast your variables into the right data types. Even if you are passing in NULLs, sometimes DB2 wants you to cast the NULL to the data type of the target column.
Here is another answer I have on the topic.
I was looking for a way to combine multiple returned rows into a single row on a db2 database (I have an application that can query a database, but will only work if a single row is returned). I found this solution which worked pretty well and was a lot easier than using recursive SQL. However, I ran into a problem when I tried to include a column that was set as TIMESTAMP instead of VARCHAR.
So how can I make this work if a column is a TIMESTAMP type?
Error:
SQL0440N No authorized routine named "XMLTEXT" of type "FUNCTION" having
compatible arguments was found. SQLSTATE=42884
SQL0440N No authorized routine named "XMLTEXT" of type "FUNCTION " having compatible arguments was found.
".
Example:
select xmlserialize(
xmlagg(
xmlconcat(
xmltext(column_name),
xmltext(':'),
xmltext(content),
xmltext(','),
xmltext(DATETIMESTAMP),
xmltext(',')
)
) as varchar(10000)
)
from
yourtable
Instead of the suggested CAST you could wrap the TOCHAR` function around the timestamp value:
select xmlserialize(
xmlagg(
xmlconcat(
xmltext(column_name),
xmltext(':'),
xmltext(content),
xmltext(','),
xmltext(TO_CHAR(DATETIMESTAMP)),
xmltext(',')
)
) as varchar(10000)
)
from
yourtable
If you are on a recent version of DB2 and have LISTAGG available I would recommend to use that function. It is much faster than converting the SQL input to XML types and then converting it back. It requires some CPU cycles due to all the official rules involved.
I am working on third party data which I need to load into my postgresql database. I am running into problems where sometimes I get the time '24:00:30' when it actually should be '00:00:30'. This rejects the data.
I tried to cast but it did not work.
insert into stop_times_test trip_id, cast(arrival_time as time), feed_id, status
from external_source;
Is there any way to convert to the correct one internally?
This may work for your case:
> select '0:0:0'::time + '24:00:30'::interval;
00:00:30
Cast to interval, then cast to time:
SELECT '24:00:30'::interval::time
If you want to bulk load the data with COPY or mass INSERT make the target column data type interval and convert it to time later. This works out of the box:
ALTER TABLE mytable ALTER col1 TYPE time;
No, there is no magic way of doing it. No cast will help you. 24:00:30 is an invalid time. Period.
You could try adding that value on a varchar and then using regular expressions to update the right values and insert them on the right columns. This sort of things happen a lot when doing data transformation.