Stored procedure - get anticipated columns before fully executing statement? - snowflake-cloud-data-platform

Question

I'm working through a stored procedure and wondering if there's a way to retrieve the anticipated result column list from a sql statement before fully executing.
Scenarios:
dynamic SQL
a UDF that might vary the columns outside of our control
EX:
//inbound parameter
SET QUERY_DEFINITION_ID = 12345;
//Initial statement pulls query text from bank of queries
var sqlText = getQueryFromQueryBank(QUERY_DEFINITION_ID);
//now we run our query
var cmd = {sqlText: sqlText };
stmt = snowflake.createStatement(cmd);
What I'd like to be able to do is say "right - before you run this, give me the anticipated column list" so I can compare it to what's expected.
EX:
Expected: [col1, col2, col3, col4]
Got: [col1]
Result: Oops. Don't run.
Rationale here is that I want to short-circuit the execution if something is missing - before it potentially runs for a while. I can validate all of this after the fact, but it would be really helpful to stop early.
Any ideas very much appreciated!

Answer 1

This sample SP code shows how to get a list of columns that a query will project into the result before you run the query. It should only be used for large, long running queries because it will take a few seconds to get the column list.
There are a couple of caveats. 1) It will only return the names of the columns. It won't tell you how they were built, that is, whether they're aliased, direct from a table, calculated, etc. 2) The example query I used is straight from the Snowflake documentation here https://docs.snowflake.com/en/user-guide/sample-data-tpcds.html#functional-query-definition. For convenience, I minimized the query to a single line. The output of the columns includes object qualifiers in addition to the column names, so V1.I_CATEGORY, V1.D_YEAR, V1.D_MOY, etc. If you don't want them to make it easier to compare names, you can strip off the qualifiers using the JavaScript split function on the dot and take index 1 of the resulting array.
create or replace procedure EXPLAIN_BEFORE_RUNNING()
returns string
language javascript
execute as caller
as
$$
// Set the context for the session to the TPC-H sample data:
executeNonQuery("use schema snowflake_sample_data.tpcds_sf10tcl;");
// Here's a complex query from the Snowflake docs (minimized to one line for convienience):
var sql = `with v1 as( select i_category, i_brand, cc_name, d_year, d_moy, sum(cs_sales_price) sum_sales, avg(sum(cs_sales_price)) over(partition by i_category, i_brand, cc_name, d_year) avg_monthly_sales, rank() over (partition by i_category, i_brand, cc_name order by d_year, d_moy) rn from item, catalog_sales, date_dim, call_center where cs_item_sk = i_item_sk and cs_sold_date_sk = d_date_sk and cc_call_center_sk= cs_call_center_sk and ( d_year = 1999 or ( d_year = 1999-1 and d_moy =12) or ( d_year = 1999+1 and d_moy =1)) group by i_category, i_brand, cc_name , d_year, d_moy), v2 as( select v1.i_category ,v1.d_year, v1.d_moy ,v1.avg_monthly_sales ,v1.sum_sales, v1_lag.sum_sales psum, v1_lead.sum_sales nsum from v1, v1 v1_lag, v1 v1_lead where v1.i_category = v1_lag.i_category and v1.i_category = v1_lead.i_category and v1.i_brand = v1_lag.i_brand and v1.i_brand = v1_lead.i_brand and v1.cc_name = v1_lag.cc_name and v1.cc_name = v1_lead.cc_name and v1.rn = v1_lag.rn + 1 and v1.rn = v1_lead.rn - 1) select * from v2 where d_year = 1999 and avg_monthly_sales > 0 and case when avg_monthly_sales > 0 then abs(sum_sales - avg_monthly_sales) / avg_monthly_sales else null end > 0.1 order by sum_sales - avg_monthly_sales, 3 limit 100;`;
// Before actually running the query, generate an explain plan.
executeNonQuery("explain " + sql);
// Now read the column list from the explain plan from the result set.
var columnList = executeSingleValueQuery("COLUMN_LIST", `select "expressions" as COLUMN_LIST from table(result_scan(last_query_id())) where "operation" = 'Result';`);
// For now, just exit with the column list as the output...
return columnList;
// Your code here...
// Helper functions:
function executeNonQuery(queryString) {
var out = '';
cmd = {sqlText: queryString};
stmt = snowflake.createStatement(cmd);
var rs;
rs = stmt.execute();
}
function executeSingleValueQuery(columnName, queryString) {
var out;
cmd1 = {sqlText: queryString};
stmt = snowflake.createStatement(cmd1);
var rs;
try{
rs = stmt.execute();
rs.next();
return rs.getColumnValue(columnName);
}
catch(err) {
if (err.message.substring(0, 18) == "ResultSet is empty"){
throw "ERROR: No rows returned in query.";
} else {
throw "ERROR: " + err.message.replace(/\n/g, " ");
}
}
return out;
}
$$;
call Explain_Before_Running();