Index suggestion engine for relational databases
Creating and executing flow plans by performing at least the following: obtaining a run-time flow plan that comprises a trigger, a first operation, and a second operation, wherein the first operation precedes the second operation within the run-time flow plan and one or more input values of the second operation are linked to the first operation, determining whether one or more conditions of the trigger are met, execute the first operation based at least on the determination that the one or more conditions of the trigger are met, monitoring whether the second operation is ready for execution based at least on a determination that the one or more input values of a second action operation are ready, and executing the second action operation when the second action operation has been identified as ready for execution.
1. A system, comprising:
a non-transitory memory; and
one or more hardware processors configured to read instructions from the non-transitory memory to cause the system to:
receive a database query;
parse the database query to identify a plurality of columns in one or more database tables;
sort at least some columns of the identified plurality of columns based on a database operation in the database query;
determine a histogram of values for each column of the sorted columns based on characteristics of fields in each column;
determine a total weight for each column of the sorted columns based on the histogram;
select a column from the sorted columns based on the total weight for each column; and
generate a suggested database index based on the selected column.
2. The system of claim 1 , wherein a first column of the suggested database index comprises the selected column.
3. The system of claim 1 , wherein the total weight comprises an indication of a cardinality of each column.
4. The system of claim 3 , wherein selecting the columns comprises selecting the column having a highest indicated cardinality.
5. The system of claim 3 , further comprising selecting a second column for the suggested database index based on the total weight for the second column as compared to other columns of the sorted columns.
6. The system of claim 1 , wherein the database query comprises database operations on two or more tables, and further comprising:
selecting a driving table based on a combined total weight of columns associated with each table, and wherein the suggested database index is based on the driving table.
7. The system of claim 1 , wherein the selected column is based on a column referenced by a WHERE clause in the database query.
8. A method for suggesting a database index, comprising:
receiving a database query;
parsing the database query to identify a plurality of columns in one or more database tables;
sorting at least some columns of the identified plurality of columns based on a database operation in the database query;
determining a histogram of values for each column of the sorted columns based on characteristics of fields in each column;
determining a total weight for each column of the sorted columns based on the histogram;
selecting a column from the sorted columns based on the total weight for each column; and
generating a suggested database index based on the selected column.
9. The method of claim 8 , wherein a first column of the suggested database index comprises the selected column.
10. The method of claim 8 , wherein the total weight comprises an indication of a cardinality of each column.
11. The method of claim 10 , wherein selecting the column comprises selecting the column having a highest indicated cardinality.
12. The method of claim 10 , further comprising selecting a second column for the suggested database index based on the total weight for the second column as compared to other columns of the sorted columns.
13. The method of claim 8 , wherein the database query comprises database operations on two or more tables, and further comprising:
selecting a driving table based on a combined total weight of columns associated with each table, and wherein the suggested database index is based on the driving table.
14. The method of claim 8 , wherein the selected column is based on a column referenced by a WHERE clause in the database query.
15. A non-transitory computer readable medium containing instructions that, when executed by one or more processors cause a programmable device to:
receive a database query;
parse the database query to identify a plurality of columns in one or more database tables;
sort at least some columns of the identified plurality of columns based on a database operation in the database query;
determine a histogram of values for each column of the sorted columns based on characteristics of fields in each column;
determine a total weight for each column of the sorted columns based on the histogram;
select a column from the sorted columns based on the total weight for each column; and
generate a suggested database index based on the selected column.
16. The non-transitory computer readable medium of claim 15 , wherein a first column of the suggested database index comprises the selected column.
17. The non-transitory computer readable medium of claim 15 , wherein the total weight comprises an indication of a cardinality of each column.
18. The non-transitory computer readable medium of claim 17 , wherein selecting the columns comprises selecting the column having a highest indicated cardinality.
19. The non-transitory computer readable medium of claim 17 , further comprising selecting a second column for the suggested database index based on the total weight for the second column as compared to other columns of the sorted columns.
20. The non-transitory computer readable medium of claim 15 , wherein the database query comprises database operations on two or more tables, and further comprising:
selecting a driving table based on a combined total weight of columns associated with each table, and wherein the suggested database index is based on the driving table.