This document discusses performance improvements and optimizations for MySQL NDB Cluster 8.0 based on TPC-H benchmark results. Key points include: - Using NVMe disks, SQL and disk data performance is now almost on par with memory. - Various configuration optimizations are shown to improve TPC-H latency for queries, including collocating MySQL servers and data nodes, optimized spinning, and increasing logical data memory partitions. - NDB parallel query architecture can scale query performance up to 12 logical data memory partitions for most TPC-H queries, with future work aimed at further optimizations.

1. Copyright © 2020 Oracle and/or its affiliates.
MySQL NDB Cluster 8.0,
TPC-H Benchmarks
MySQL Cluster Development
Mikael Ronström

2. Faster SQL and disk data
• On modern NVMe disk data almost at par with
memory

3. NDB
Mgmt Server
MySQL Server
NDB
Mgmt Server
MySQL Server
NDB Data Node NDB Data Node
……………………… MySQL App
Load
Balancer
MySQL App
Scalable Cluster Setup for MySQL Cluster 8.0

4. Latency Optimised Small Cluster Setup for MySQL Cluster 8.0
Computer Computer
Computer
Small Computer
……. n Servers/
VMs/
Containers
2 Servers/
VMs/
Containers
MySQL
App
MySQL
App
MySQL Server
NDB Data Node
NDB Mgm Server
2 Small Servers/
VMs/
Containers
Computer
Small Computer
MySQL Server
NDB Data Node
NDB Mgm Server
Shared Memory Connection Shared Memory Connection
Load
Balancer

5. TPC-H Improvement in 8.0.20 vs 7.6
(SF=10)
PercentageimprovementwithNDB8.0.20
1
10
100
1000
10000
Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 Q22
Improvements 8.0.20 vs 7.6.12

6. TPC-H Latency improvement with
Colocated MySQL Server and NDB Data Node
Percentageimprovementwithcolocation
0
35
70
105
140
TPC-H Queries
Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 Q22
Colocated improvement

7. TPC-H Latency improvement with
LatencyOptimisedSpinning
Percentageimprovementwith
LatencyOptimisedSpinning
0
15
30
45
60
TPC-H Queries
Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 Q22
LatencyOptimisedSpinning

8. TPC-H Latency Improvement with
Colocation AND LatencyOptimisedSpinning
PercentageimprovementColocated+
LatencyOptimisedSpinning
0
60
120
180
240
300
TPC-H Queries
Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 Q22
Colocated+LatencyOptimisedSpinning

9. TPC-H Latency Improvement going from
6 LDMs to 12 LDMs
Percentagechange12LDMsvs6LDMs
-25
0
25
50
75
100
TPC-H Queries
Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 Q22
12LDM vs 6 LDM

10. TPC-H NDB vs InnoDB
2-node HA fully-replicated NDB compared to standalone local InnoDB
PercentagedifferenceNDBvsInnoDB
-1500
0
1500
3000
4500
6000
TPC-H Queries
Q2 Q3 *) Q4 Q5 Q6 Q7 Q8 *) Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 Q19 Q20 Q21 Q22
NDB vs InnoDB

11. NDB Execution architecture
Parallel Query, 2 Data Node, Read Backup
MySQL Server
MySQL
Connection
Thread
NDB API
Receive
Thread
NDB
Data Node
Receive
Thread
TC
Thread
(Join Exec)
TC
Thread
(Join Exec)
LDM
Thread
Select +
Project
LDM
Thread
Select +
Project
LDM
Thread
Select +
Project

12. • Single MySQL Connection Thread
• Single NDB API Receive Thread (Per Query)
• 2 TC threads per Node Group
• Network Bandwidth
Potential Bottlenecks for
NDB Parallel Query

13. • Primary Key lookup = O(1), a few microseconds
• Unique Key lookup = O(1) is 2 Primary Key lookups
• Full table scan = NumPartitions * start_cost + NumRows *
scan_cost
• Partition Pruned Range scan = start_cost + NumRangeRows *
scan_cost
• Range scan not pruned = NumPartitions * start_cost +
NumRangeRows * scan_cost
NDB Query Costs

14. • Filtering scales almost perfectly
• TPC-H scales to 12 LDMs for most queries
• 24 LDMs brings only change to a few queries, some negative,
some positive
• Future work to push join filtering to TC threads
• Future work to push more functions to LDM threads
• More work on improving NDB Cost Model
Scalability of Parallel Query in NDB 8.0.20