Memory and concurrency limits for dedicated SQL pool in Azure Synapse Analytics
View the memory and concurrency limits allocated to the various performance levels and resource classes in Azure Synapse Analytics.
Note
Workload management workload groups provide more flexibility for configuring resources per request and concurrency than dynamic or static resource classes. See Workload Groups and the CREATE WORKLOAD GROUP syntax for further details.
Data warehouse capacity settings
The following tables show the maximum capacity for the data warehouse at different performance levels. To change the performance level, see Scale compute - portal.
Service Levels
The service levels range from DW100c to DW30000c.
Performance level | Compute nodes | Distributions per Compute node | Memory per data warehouse (GB) |
---|---|---|---|
DW100c | 1 | 60 | 60 |
DW200c | 1 | 60 | 120 |
DW300c | 1 | 60 | 180 |
DW400c | 1 | 60 | 240 |
DW500c | 1 | 60 | 300 |
DW1000c | 2 | 30 | 600 |
DW1500c | 3 | 20 | 900 |
DW2000c | 4 | 15 | 1200 |
DW2500c | 5 | 12 | 1500 |
DW3000c | 6 | 10 | 1800 |
DW5000c | 10 | 6 | 3000 |
DW6000c | 12 | 5 | 3600 |
DW7500c | 15 | 4 | 4500 |
DW10000c | 20 | 3 | 6000 |
DW15000c | 30 | 2 | 9000 |
DW30000c | 60 | 1 | 18000 |
The maximum service level is DW30000c, which has 60 Compute nodes and one distribution per Compute node. For example, a 600 TB data warehouse at DW30000c processes approximately 10 TB per Compute node.
Note
Synapse Dedicated SQL pool is an evergreen platform service. Under shared responsibility model in the cloud, Microsoft continues to invest in advancements to underlying software and hardware which host dedicated SQL pool. As a result, the number of nodes or the type of computer hardware which underpins a given performance level (SLO) may change. The number of compute nodes listed here are provided as a reference, and shouldn't be used for sizing or performance purposes. Irrespective of number of nodes or underlying infrastructure, Microsoft's goal is to deliver performance in accordance with SLO; hence, we recommend that all sizing exercises must use cDWU as a guide. For more information on SLO and compute Data Warehouse Units, see Data Warehouse Units (DWUs) for dedicated SQL pool (formerly SQL DW).
Concurrency maximums for workload groups
With the introduction of workload groups, the concept of concurrency slots no longer applies. Resources per request are allocated on a percentage basis and specified in the workload group definition. However, even with the removal of concurrency slots, there are minimum amounts of resources needed per queries based on the service level. The below table defined the minimum amount of resources needed per query across service levels and the associated concurrency that can be achieved.
Service Level | Maximum concurrent queries | Min % supported for REQUEST_MIN_RESOURCE_GRANT_PERCENT |
---|---|---|
DW100c | 4 | 25% |
DW200c | 8 | 12.5% |
DW300c | 12 | 8% |
DW400c | 16 | 6.25% |
DW500c | 20 | 5% |
DW1000c | 32 | 3% |
DW1500c | 32 | 3% |
DW2000c | 48 | 2% |
DW2500c | 48 | 2% |
DW3000c | 64 | 1.5% |
DW5000c | 64 | 1.5% |
DW6000c | 128 | 0.75% |
DW7500c | 128 | 0.75% |
DW10000c | 128 | 0.75% |
DW15000c | 128 | 0.75% |
DW30000c | 128 | 0.75% |
Concurrency maximums for resource classes
To ensure each query has enough resources to execute efficiently, Synapse SQL tracks resource utilization by assigning concurrency slots to each query. The system puts queries into a queue based on importance and concurrency slots. Queries wait in the queue until enough concurrency slots are available. Importance and concurrency slots determine CPU prioritization. For more information, see Analyze your workload
Static resource classes
The following table shows the maximum concurrent queries and concurrency slots for each static resource class.
Service Level | Maximum concurrent queries | Concurrency slots available | Slots used by staticrc10 | Slots used by staticrc20 | Slots used by staticrc30 | Slots used by staticrc40 | Slots used by staticrc50 | Slots used by staticrc60 | Slots used by staticrc70 | Slots used by staticrc80 |
---|---|---|---|---|---|---|---|---|---|---|
DW100c | 4 | 4 | 1 | 2 | 4 | 4 | 4 | 4 | 4 | 4 |
DW200c | 8 | 8 | 1 | 2 | 4 | 8 | 8 | 8 | 8 | 8 |
DW300c | 12 | 12 | 1 | 2 | 4 | 8 | 8 | 8 | 8 | 8 |
DW400c | 16 | 16 | 1 | 2 | 4 | 8 | 16 | 16 | 16 | 16 |
DW500c | 20 | 20 | 1 | 2 | 4 | 8 | 16 | 16 | 16 | 16 |
DW1000c | 32 | 40 | 1 | 2 | 4 | 8 | 16 | 32 | 32 | 32 |
DW1500c | 32 | 60 | 1 | 2 | 4 | 8 | 16 | 32 | 32 | 32 |
DW2000c | 48 | 80 | 1 | 2 | 4 | 8 | 16 | 32 | 64 | 64 |
DW2500c | 48 | 100 | 1 | 2 | 4 | 8 | 16 | 32 | 64 | 64 |
DW3000c | 64 | 120 | 1 | 2 | 4 | 8 | 16 | 32 | 64 | 64 |
DW5000c | 64 | 200 | 1 | 2 | 4 | 8 | 16 | 32 | 64 | 128 |
DW6000c | 128 | 240 | 1 | 2 | 4 | 8 | 16 | 32 | 64 | 128 |
DW7500c | 128 | 300 | 1 | 2 | 4 | 8 | 16 | 32 | 64 | 128 |
DW10000c | 128 | 400 | 1 | 2 | 4 | 8 | 16 | 32 | 64 | 128 |
DW15000c | 128 | 600 | 1 | 2 | 4 | 8 | 16 | 32 | 64 | 128 |
DW30000c | 128 | 1200 | 1 | 2 | 4 | 8 | 16 | 32 | 64 | 128 |
Dynamic resource classes
The following table shows the maximum concurrent queries and concurrency slots for each dynamic resource class. Dynamic resource classes use a 3-10-22-70 memory percentage allocation for small-medium-large-xlarge resource classes across service level DW1000c to DW30000c. For memory allocation under DW1000c, please refer to the document dynamic resource class.
Service Level | Maximum concurrent queries | Concurrency slots available | Slots used by smallrc | Slots used by mediumrc | Slots used by largerc | Slots used by xlargerc |
---|---|---|---|---|---|---|
DW100c | 4 | 4 | 1 | 1 | 1 | 2 |
DW200c | 8 | 8 | 1 | 1 | 1 | 5 |
DW300c | 12 | 12 | 1 | 1 | 2 | 8 |
DW400c | 16 | 16 | 1 | 1 | 3 | 11 |
DW500c | 20 | 20 | 1 | 2 | 4 | 14 |
DW1000c | 32 | 40 | 1 | 4 | 8 | 28 |
DW1500c | 32 | 60 | 1 | 6 | 13 | 42 |
DW2000c | 32 | 80 | 2 | 8 | 17 | 56 |
DW2500c | 32 | 100 | 3 | 10 | 22 | 70 |
DW3000c | 32 | 120 | 3 | 12 | 26 | 84 |
DW5000c | 32 | 200 | 6 | 20 | 44 | 140 |
DW6000c | 32 | 240 | 7 | 24 | 52 | 168 |
DW7500c | 32 | 300 | 9 | 30 | 66 | 210 |
DW10000c | 32 | 400 | 12 | 40 | 88 | 280 |
DW15000c | 32 | 600 | 18 | 60 | 132 | 420 |
DW30000c | 32 | 1200 | 36 | 120 | 264 | 840 |
When there are not enough concurrency slots free to start query execution, queries are queued and executed based on importance. If there is equivalent importance, queries are executed on a first-in, first-out basis. As a queries finishes and the number of queries and slots fall below the limits, Azure Synapse Analytics releases queued queries.
Next steps
To learn more about how to leverage resource classes to optimize your workload further please review the following articles: