-
Notifications
You must be signed in to change notification settings - Fork 3
/
cas
84 lines (58 loc) · 4.23 KB
/
cas
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
https://chatgpt.com/c/88c63276-7d35-4ee5-8576-5e9d9101643b
https://chatgpt.com/c/c2548222-487d-4f38-aa50-03c4e6d21e9c
Improving read latency in Apache Cassandra, especially with a large database size like yours (65 TBs) spread across multiple data centers (DCs), involves tuning several configuration parameters to optimize query performance. Here are some key Cassandra parameters and considerations that can help improve read request times:
### 1. **Partition Size and Compaction**
- **max_partition_size**
- Adjusting `max_partition_size` can help control the size of partitions, which affects read performance. Large partitions can lead to increased read latency.
- Example: `max_partition_size = 100 MB`
- **compaction throughput**
- Setting `compaction_throughput_mb_per_sec` appropriately can optimize how quickly data is compacted, affecting read latency indirectly by managing disk I/O efficiently.
- Example: `compaction_throughput_mb_per_sec = 128`
### 2. **Memtable Configuration**
- **memtable_flush_writers**
- Increasing `memtable_flush_writers` can parallelize memtable flushes, potentially reducing read latency by optimizing disk writes.
- Example: `memtable_flush_writers = 4`
- **memtable_heap_space_in_mb**
- Adjust `memtable_heap_space_in_mb` to ensure sufficient heap space is allocated for memtables, which store recent writes before flushing to disk.
- Example: `memtable_heap_space_in_mb = 2048`
### 3. **Read Performance**
- **read_request_timeout_in_ms**
- Increase `read_request_timeout_in_ms` if read operations are timing out frequently due to heavy load or large data retrieval.
- Example: `read_request_timeout_in_ms = 10000` (10 seconds)
- **concurrent_reads**
- Adjust `concurrent_reads` to control the number of concurrent read requests per node, balancing between throughput and latency.
- Example: `concurrent_reads = 64`
### 4. **Tuning for Large Dataset**
- **compaction_large_partition_warning_threshold_mb**
- Set `compaction_large_partition_warning_threshold_mb` to identify large partitions that may impact read performance negatively.
- Example: `compaction_large_partition_warning_threshold_mb = 1000`
- **tombstone_warn_threshold**
- Adjust `tombstone_warn_threshold` to manage tombstone (deleted data marker) thresholds efficiently, preventing excessive tombstone creation which can affect read performance.
- Example: `tombstone_warn_threshold = 1000`
### 5. **Network and Replication**
- **read_consistency_level**
- Adjust `read_consistency_level` based on your application's requirements and data consistency needs. Lower consistency levels (`ONE`, `LOCAL_ONE`) can improve read latency but may sacrifice consistency.
- Example: `read_consistency_level = ONE`
- **stream_throughput_outbound_megabits_per_sec**
- Ensure `stream_throughput_outbound_megabits_per_sec` is appropriately set to manage inter-node communication bandwidth during data streaming and replication.
- Example: `stream_throughput_outbound_megabits_per_sec = 200`
### Additional Considerations:
- **Monitoring and Benchmarking**: Regularly monitor cluster performance metrics using tools like `nodetool` and review Cassandra's logs (`system.log`) for potential bottlenecks or warnings.
- **Schema Design**: Optimize table schema and data modeling to minimize partition hotspots and optimize data retrieval patterns.
- **Hardware and Storage**: Ensure sufficient CPU, memory, and storage resources across all nodes to handle the workload efficiently.
- **Cassandra Version**: Keep Cassandra up-to-date with the latest stable release to benefit from performance improvements and bug fixes.
### Example Configuration:
Here’s how you might configure some of these parameters in your `cassandra.yaml` configuration file:
```yaml
max_partition_size: 100 MB
compaction_throughput_mb_per_sec: 128
memtable_flush_writers: 4
memtable_heap_space_in_mb: 2048
read_request_timeout_in_ms: 10000
concurrent_reads: 64
compaction_large_partition_warning_threshold_mb: 1000
tombstone_warn_threshold: 1000
read_consistency_level: ONE
stream_throughput_outbound_megabits_per_sec: 200
```
Adjust these values based on your specific workload characteristics and performance testing results to achieve optimal read latency and throughput in your Cassandra cluster.