I have a json like this in an Athena table:
input
[14587979, {ke1:4,ke2:4}]
I would like to get the fist value "14587979"
but when I use json_extract like this:
json_extract(input, "$[0]") as id
I get the below error
Query execution failed
Reason:
SQL Error [100071] [HY000]: [Simba]AthenaJDBC An error has been thrown from the AWS Athena client. SYNTAX_ERROR: line 3:22: Column '$[0]' cannot be resolved
how Can I get the first value?
Use single quotes, double quotes are used to escape column/table/schema names (if for some example the name contains restricted character like space):
select json_extract('[14587979, {ke1:4,ke2:4}]', '$[0]');
Output:
_col0
14587979
Related
I have a large data set on dbeaver (postgreSQL), and I am trying to filter for the following:
select * from raw_data_file where data_file_group_id = 2592 and dl_date = 2022-06-15
However, I am getting an error for the dl_date part of the filter- any suggestions?
SQL Error [42883]: ERROR: operator does not exist: date = integer¶ Hint: No operator matches the given name and argument types. You might need to add explicit type casts.¶ Position: 74
Stu's comment is correct. Use quotes, single quotes, otherwise the subexpression looks like a couple of subtractions.
I'm using try_cast in snowflake to convert any long values in sql to NULL.
Here is my code:
When I try running the above code, I'm getting the error as below:
I'm flattening a JSON array and using try_cast to make any large values to NULL because I was getting an error Failed to cast variant value {numberLong: -8301085358432}
SELECT try_cast(item.value:price) as item_price,
try_cast(item.value:total_price_bill) as items_total_price
FROM table, LATERAL FLATTEN(input => products) item
Error:
SQL compilation error error at line 1 at position ')'.
I don't understand where I'm doing wrong
you are using wrong syntax for try_cast. according to snowflake documentations the syntax is :
TRY_CAST( <source_string_expr> AS <target_data_type> )
and also note:
Only works for string expressions.
target_data_type must be one of the following:
VARCHAR (or any of its synonyms)
NUMBER (or any of its synonyms)
DOUBLE
BOOLEAN
DATE
TIME
TIMESTAMP, TIMESTAMP_LTZ, TIMESTAMP_NTZ, or TIMESTAMP_TZ
so for example you have to have something like this if item.value:price is string:
select try_cast(item.value:price as NUMBER) as item_price,
....
I'm trying to get a substring from the value of a column and I'm getting the following error Argument data type varchar is invalid for argument 2 of substring function.
The column type is NvarChar(50) and is a system column for an application, so I can't modify it.
Ideally I'd just be able to select the substring as part of the query without having to alter the table, or create a view or another table.
Here's my query
SELECT SUBSTRING(INVOICE__, ':', 1)
FROM dwsystem.dbo.DWGroup
Im trying to select only everything in the string after a specific character. In this case the : character.
Use charindex with : as the first argument
select substring(invoice__,charindex(':',invoice__)+1,len(invoice__))
from dwsystem.dbo.dwgroup
SUBSTRING parameter is start position and end position so both parameter will be number like below
SELECT SUBSTRING(INVOICE__, 1, 1)
FROM dwsystem.dbo.DWGroup
you can use SUBSTRING_INDEX as you used mysql
SELECT SUBSTRING_INDEX(INVOICE__,':',-1);
example
SELECT SUBSTRING_INDEX('mytestpage:info',':',-1); it will return
info
I'm trying to load some data from stage to relational environment and something is happening I can't figure out.
I'm trying to run the following query:
SELECT
CAST(SPLIT_PART(some_field,'_',2) AS BIGINT) cmt_par
FROM
public.some_table;
The some_field is a column that has data with two numbers joined by an underscore like this:
some_field -> 38972691802309_48937927428392
And I'm trying to get the second part.
That said, here is the error I'm getting:
[Amazon](500310) Invalid operation: Invalid digit, Value '1', Pos 0,
Type: Long
Details:
-----------------------------------------------
error: Invalid digit, Value '1', Pos 0, Type: Long
code: 1207
context:
query: 1097254
location: :0
process: query0_99 [pid=0]
-----------------------------------------------;
Execution time: 2.61s
Statement 1 of 1 finished
1 statement failed.
It's literally saying some numbers are not valid digits. I've already tried to get the exactly data which is throwing the error and it appears to be a normal field like I was expecting. It happens even if I throw out NULL fields.
I thought it would be an encoding error, but I've not found any references to solve that.
Anyone has any idea?
Thanks everybody.
I just ran into this problem and did some digging. Seems like the error Value '1' is the misleading part, and the problem is actually that these fields are just not valid as numeric.
In my case they were empty strings. I found the solution to my problem in this blogpost, which is essentially to find any fields that aren't numeric, and fill them with null before casting.
select cast(colname as integer) from
(select
case when colname ~ '^[0-9]+$' then colname
else null
end as colname
from tablename);
Bottom line: this Redshift error is completely confusing and really needs to be fixed.
When you are using a Glue job to upsert data from any data source to Redshift:
Glue will rearrange the data then copy which can cause this issue. This happened to me even after using apply-mapping.
In my case, the datatype was not an issue at all. In the source they were typecast to exactly match the fields in Redshift.
Glue was rearranging the columns by the alphabetical order of column names then copying the data into Redshift table (which will
obviously throw an error because my first column is an ID Key, not
like the other string column).
To fix the issue, I used a SQL query within Glue to run a select command with the correct order of the columns in the table..
It's weird why Glue did that even after using apply-mapping, but the work-around I used helped.
For example: source table has fields ID|EMAIL|NAME with values 1|abcd#gmail.com|abcd and target table has fields ID|EMAIL|NAME But when Glue is upserting the data, it is rearranging the data by their column names before writing. Glue is trying to write abcd#gmail.com|1|abcd in ID|EMAIL|NAME. This is throwing an error because ID is expecting a int value, EMAIL is expecting a string. I did a SQL query transform using the query "SELECT ID, EMAIL, NAME FROM data" to rearrange the columns before writing the data.
Hmmm. I would start by investigating the problem. Are there any non-digit characters?
SELECT some_field
FROM public.some_table
WHERE SPLIT_PART(some_field, '_', 2) ~ '[^0-9]';
Is the value too long for a bigint?
SELECT some_field
FROM public.some_table
WHERE LEN(SPLIT_PART(some_field, '_', 2)) > 27
If you need more than 27 digits of precision, consider a decimal rather than bigint.
If you get error message like “Invalid digit, Value ‘O’, Pos 0, Type: Integer” try executing your copy command by eliminating the header row. Use IGNOREHEADER parameter in your copy command to ignore the first line of the data file.
So the COPY command will look like below:
COPY orders FROM 's3://sourcedatainorig/order.txt' credentials 'aws_access_key_id=<your access key id>;aws_secret_access_key=<your secret key>' delimiter '\t' IGNOREHEADER 1;
For my Redshift SQL, I had to wrap my columns with Cast(col As Datatype) to make this error go away.
For example, setting my columns datatype to Char with a specific length worked:
Cast(COLUMN1 As Char(xx)) = Cast(COLUMN2 As Char(xxx))
I'm trying to find a maximum number of a string. First I try to turn it into an Integer field first, but keep getting error message for example:
Conversion failed when converting the nvarchar value '3,029' to data type int.
I tried to replace the possible single quotation marks into a blank char like below:
SELECT TOP 100 (CAST(REPLACE(a.PortNumber,'''','') AS INT)) FROM dbo.Account a
WHERE nwp_AccountType = 121710000
ORDER BY (CAST(REPLACE(a.PortNumber,'''','') AS INT)) DESC
But still getting the same error message again.
Any idea?
The error is in your REPLACE statement
(CAST(REPLACE(a.PortNumber,',','') AS INT))
The problem was the comma, I added another replace for the comma to an empty string and it works.