Efficient way to join by levenshtein in Hive or Impala - hadoop

Question

I have two tables one includes about 17K (NLIST) records while the other 57K (FNAMES).
I would like to join the both by comparing the records using levenshtein formula.
Here is the example for the content of tables:
Table NLIST:
+------+-------------+
| ID | S_NAME |
+------+-------------+
| 1 | Avi |
| 2 | Moshe |
| 3 | David |
....
Table FNAMES:
+------+-------------+
| ID | NICKNAMES |
+------+-------------+
| 1 | Avile |
| 2 | Dudi |
| 3 | Moshiko |
| 4 | Avi |
| 5 | DAVE |
....
The above tables are just examples. In the real case the names column can include more than one word.
The required result should be:
+------+-------------+--------+
| ID | NICKNAMES | S_NAME |
+------+-------------+--------+
| 1 | Avile | Avi |
| 2 | Dudi | David |
| 3 | Moshiko | Moshe |
| 4 | Avi | Avi |
| 5 | DAVE | David |
...
Here is the code I use:
select FNAMES.NICKNAMES, NLIST.S_NAME
from NICKNAMES
LEFT OUTER JOIN NLIST
ON(true)
WHERE levenshtein (FNAMES.NICKNAMES, NLIST.S_NAME) <=4
The above code runs for a very long time and I stopped its running.
How can I make it run in a reasonable time?
In addition, I think the levenshtein distance depends on the length of the words. How can I find the optimal value for the distance (in this case I chose 4 arbitrarily)?

Answer 1

Hive Table performance is depends upon various point .
Query enginee
File format
use VECTORIZATION set hive.vectorized.execution.enabled = true;set hive.vectorized.execution.reduce.enabled = true;
If you have good server you can try with Impala and definitely it is faster than Hive.
You can do the fine tuning of impala which will give you an edge to execute this query faster .Tuning Impala for Performance