Pruning index for optimization of pattern matching queries
A query directed at a source table organized into a set of batch units is received. The query includes a pattern matching predicate that specifies a search pattern. A set of N-grams are generated based on the search pattern. A pruning index associated with the source table is accessed. The pruning index comprises a set of filters that index distinct N-grams in each column of the source table. The pruning index is used to identify a subset of batch units to scan for matching data based on the set of N-grams generated for the search pattern. The query is processed by scanning the subset of batch units.
1. A database system comprising:
at least one hardware processor; and
at least one memory storing instructions that cause the at least one hardware processor to perform operations comprising:
receiving a query directed at a source table organized into a set of batch units, the query including a pattern matching predicate specifying a search pattern;
generating a set of N-grams based on the search pattern;
accessing a pruning index associated with the source table, the pruning index comprising a set of filters that index distinct N-grams in each column of the source table;
identifying, using the set of N-grams generated based on the search pattern, a subset of batch units to scan for matching data based on the pruning index associated with the source table; and
processing the query by scanning the subset of batch units.
2. The database system of claim 1 , wherein:
the operations further comprise preprocessing the search pattern before generating the set of N-grams, and
the preprocessing of the search pattern includes generating one or more preprocessed variants of the search pattern.
3. The database system of claim 2 , wherein the preprocessing of the search pattern includes generating a case-agnostic variant of the search pattern.
4. The database system of claim 2 , wherein the preprocessing of the search pattern includes generating one or more misspelled variants of the search pattern.
5. The database system of claim 2 , wherein the preprocessing of the search pattern includes generating one or more synonymous variants corresponding to synonyms of the search pattern.
6. The database system of claim 2 , wherein the preprocessing of the search pattern includes generating a variant with one or more special characters to mark a start and end of the search pattern.
7. The database system of claim 1 , wherein identifying the subset of batch units comprises:
generating a set of fingerprints based on the set of N-grams; and
comparing the set of fingerprints to the pruning index.
8. The database system of claim 7 , wherein generating the set of fingerprints based on the set of N-grams comprises computing a hash for each N-gram in the set of N-grams.
9. The database system of claim 7 , wherein identifying the subset of batch units further comprises:
identifying one or more values in the pruning index that match one or more fingerprints in the set of fingerprints; and
identifying the subset of batch units based on the one or more values.
10. The database system of claim 1 , wherein the pruning index comprises a set of filters, each filter in the set of filters corresponding to one batch unit in the set of batch units.
11. A method comprising:
receiving a query directed at a source table organized into a set of batch units, the query including a pattern matching predicate specifying a search pattern;
generating a set of N-grams based on the search pattern;
accessing a pruning index associated with the source table, the pruning index comprising a set of filters that index distinct N-grams in each column of the source table;
identifying, using the set of N-grams generated based on the search pattern, a subset of batch units to scan for matching data based on the pruning index associated with the source table; and
processing the query by scanning the subset of batch units.
12. The method of claim 11 , further comprising preprocessing the search pattern before generating the set of N-grams, wherein the preprocessing of the search pattern includes generating one or more preprocessed variants of the search pattern.
13. The method of claim 12 , wherein the preprocessing of the search pattern includes generating a case-agnostic variant of the search pattern.
14. The method of claim 12 , wherein the preprocessing of the search pattern includes generating one or more misspelled variants of the search pattern.
15. The method of claim 12 , wherein the preprocessing of the search pattern includes generating one or more synonymous variants corresponding to synonyms of the search pattern.
16. The method of claim 12 , wherein the preprocessing of the search pattern includes generating a variant with one or more special characters to mark a start and end of the search pattern.
17. The method of claim 11 , wherein identifying the subset of batch units comprises:
generating a set of fingerprints based on the set of N-grams; and
comparing the set of fingerprints to the pruning index.
18. The method of claim 17 , wherein generating the set of fingerprints based on the set of N-grams comprises computing a hash for each N-gram in the set of N-grams.
19. The method of claim 17 , wherein identifying the subset of batch units further comprises:
identifying one or more values in the pruning index that match one or more fingerprints in the set of fingerprints; and
identifying the subset of batch units based on the one or more values.
20. The method of claim 11 , wherein the pruning index comprises a set of filters, each filter in the set of filters corresponding to one batch unit in the set of batch units.
21. A computer-storage medium comprising instructions that, when executed by one or more processors of a machine, configure the machine to perform operations comprising:
receiving a query directed at a source table organized into a set of batch units, the query including a pattern matching predicate specifying a search pattern;
generating a set of N-grams based on the search pattern;
accessing a pruning index associated with the source table, the pruning index comprising a set of filters that index distinct N-grams in each column of the source table;
identifying, using the set of N-grams generated based on the search pattern, a subset of batch units to scan for matching data based on the pruning index associated with the source table; and
processing the query by scanning the subset of batch units.
22. The computer-storage medium of claim 21 , wherein:
the operations further comprise preprocessing the search pattern before generating the set of N-grams, and
the preprocessing of the search pattern includes generating one or more preprocessed variants of the search pattern.
23. The computer-storage medium of claim 22 , wherein the preprocessing of the search pattern includes generating a case-agnostic variant of the search pattern.
24. The computer-storage medium of claim 22 , wherein the preprocessing of the search pattern includes generating one or more misspelled variants of the search pattern.
25. The computer-storage medium of claim 22 , wherein the preprocessing of the search pattern includes generating one or more synonymous variants corresponding to synonyms of the search pattern.
26. The computer-storage medium of claim 22 , wherein the preprocessing of the search pattern includes generating a variant with one or more special characters to mark a start and end of the search pattern.
27. The computer-storage medium of claim 21 , wherein identifying the subset of batch units comprises:
generating a set of fingerprints based on the set of N-grams; and
comparing the set of fingerprints to the pruning index.
28. The computer-storage medium of claim 27 , wherein generating the set of fingerprints based on the set of N-grams comprises computing a hash for each N-gram in the set of N-grams.
29. The computer-storage medium of claim 27 , wherein identifying the subset of batch units further comprises:
identifying one or more values in the pruning index that match one or more fingerprints in the set of fingerprints; and
identifying the subset of batch units based on the one or more values.
30. The computer-storage medium of claim 21 , wherein the pruning index comprises a set of filters, each filter in the set of filters corresponding to one batch unit in the set of batch units.