Could someone advise what is the query execution method in PySpark? Impala query execution is faster than hive query execution however when we run the same queries via Pyspark it is taking long how would we get the impala execution method via Pyspark?
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I have a query and run it using SQL management studio. Usually, there is created one execution plan for a query in the studio. But sometimes I can catch up the duplicated execution plans for a single Query on the Azure SQL like below.
When I open the query from this plan I see the duplicated query. As if the copied query is pasted into the same query. The same in Query 1 and Query 2. See below.
Maybe someone knows why does this happen and how to avoid this behavior? How is that even possible?
P.S. Time of execution query was increased from 2 sec to 20 sec and more.
P.P.S. The warning in the Query 2
It could be that the queries were ran with different settings. I can notice that one has a warning and the other doesn't.
Reference:
https://blogs.msdn.microsoft.com/psssql/2014/04/03/i-think-i-am-getting-duplicate-query-plan-entries-in-sql-servers-procedure-cache/
I have a SQL query, first I analyzed the query by executing and it is taking less than 1 ms.
So I used the query in my spring boot app, and tried to execute it using
namedParameterJdbcTemplate.query(sqlQuery, params, new validationMapper());
but when I see the time, it is 19212ms.
Why this much time difference?
I'm running a complicated query against a Redshift cluster in which there are 4 tables used with some of them have billions of rows, and I get the following error:
failed to make a valid plan
If I limit the data, the query will run successfully.
-The Original query was an Oracle query which I've made some modifications on it, and data loaded in the tables in Redshift was also exported from Oracle.
-The query has a lot of JOINs and sub queries.
With those being said, going through the sub-queries one at a time, one of them didn't return any results, and that was the cause of this error in my case.
Fixing that particular sub-query and the main query accordingly, it worked successfully.
I am running Impala query on Hue. I want to know the execution time of each Impala query. I looked over different answers on the Internet, but I could not figure out.
impala service runs on 25000 port, there you can see all the queries and the time of execution. for quickstart node, example url is: quickstart.cloudera:25000/queries
I need to measure SPARQL query execution time. Could you please inform me what command I need to use for that? I am using Virtuoso.
Virtuoso 7 lets you get the compilation (query plan) and query execution time of a query using the profile function.
You can also enable general query logging and profiling using the prof_enable function.