1. Some TPC-H queries on Teradata and PostgreSQL
Project Partners:
Amreek Singh ( )
Chetan Vaity ( )

2. Motivation Usage of real Database Systems
Gain some experience in database tuning
Work with Teradata machine in SIT
Test Setup
Twin processors with 2GB RAM, proprietary parallel storage system
Windows 2000 Advanced Server
Teradata v4.1.2
Twin Xeon processors with 2GB RAM, RAID 5
Linux Kernel version smp
PostgreSQL v7.2.1

3. TPC-H Schema A typical manufacturing concern database
Part (200K rows)
Order (1500K rows)
Partsupp (800K rows)
Lineitem (6000K rows)
Supplier (10K rows)
Customer (150K rows)
Nation (24 rows)
Region (5 rows)
A typical manufacturing concern database
Approximately 1GB of data

4. TPC-H Query 2 Teradata Query Plan Region Nation
SELECT
s_acctbal, s_name, n_name, p_partkey, p_mfgr,
s_address, s_phone, s_comment
FROM
part, supplier, partsupp, nation, region
WHERE
p_partkey = ps_partkey
AND s_suppkey = ps_suppkey
AND p_size = 15
AND p_type like '%BRASS'
AND s_nationkey = n_nationkey
AND n_regionkey = r_regionkey
AND r_name = 'EUROPE'
AND ps_supplycost = (
min(ps_supplycost)
partsupp, supplier, nation, region )
ORDER BY
s_acctbal desc, n_name, s_name, p_partkey;
Region
Nation
Region (r_name=‘EUROPE’)
Part
Part (p_size=15) (p_type=‘%BRASS’)
Partsupp
Supplier
Teradata Query Plan

5. Analysis of query execution plans of both systems
Added indexes (B-Tree indexes on all)
Rewrote the query using “explicit join” clause
Reduced query time from 40 minutes to 2 seconds
Region
Nation
Region (r_name=‘EUROPE’)
Part
Part (p_size=15) (p_type=‘%BRASS’)
Partsupp
Supplier
PostgreSQL Query Plan

6. Query execution times Teradata t1 t2 t3 PostgreSQL Initial
31 sec
25 sec
26 sec Q2
11 sec
10 sec
1 sec Q3
2 min 15sec
2 min 11 sec
1 min 16 sec
After adding secondary index on n_nationkey on supplier table
After Collect statistics
PostgreSQL
Initial
After “ANALYZE”
After adding indexes Q6
33 sec
32 sec
30 sec Q2
40 m 19 sec
35 min 4 sec
2 sec Q3
11 min 43 sec
11 min 32 sec
1 min 11 sec

7. Conclusion: Bibliography
Query plans are very useful in database tuning
Parallel architecture under full DBMS control performs
Bibliography
PostgreSQL Documentation
Teradata Documentation
Database Tuning, Dennis Shasha