Install
openclaw skills install @huaweicloudskill/huawei-cloud-dws-spec-plannerHuawei Cloud DWS data warehouse configuration planning and sizing. Supports coupled/decoupled architecture, outputs minimum-spec plan and multi-sheet Excel report. Automatically calculates CPU cores, storage capacity, and generates structured report. Applicable to DWS cluster planning, node spec selection, data warehouse migration, capacity planning, and scale-out scenarios. Trigger words: "DWS planning", "DWS sizing", "DWS cluster planning", "DWS node spec", "data warehouse migration to DWS", "DWS scale-out", "DWS capacity planning", "DWS规划", "DWS选型", "DWS集群规划", "DWS节点规格", "数据仓库迁移DWS", "存算一体", "存算分离", "DWS扩容", "DWS容量规划"
openclaw skills install @huaweicloudskill/huawei-cloud-dws-spec-plannerChinese triggers: "DWS规划", "DWS选型", "DWS集群规划", "DWS节点规格", "数据仓库迁移DWS", "华为云DWS", "Data Warehouse Service", "DWS sizing", "存算一体", "存算分离", "日增数据量", "DWS扩容", "DWS容量规划"
English triggers: "DWS planning", "DWS sizing", "DWS cluster planning", "DWS node spec", "data warehouse migration to DWS", "Huawei Cloud DWS", "Data Warehouse Service", "coupled storage-compute", "decoupled storage-compute", "daily incremental data", "DWS scale-out", "DWS capacity planning"
Based on migration or greenfield scenarios, configuration planning is performed for both coupled and decoupled storage-compute architecture modes. The skill outputs one minimum-spec plan that satisfies requirements (minimum compute surplus under constraints), along with storage growth reserve and scale-out cadence recommendations based on daily incremental data. Functional boundary: requirement survey -> architecture mode confirmation -> CPU core calculation -> minimum-spec flavor selection -> hot data storage/cache capacity calculation -> (optional) growth reserve and scale-out cadence -> report output -> Excel generation.
Security rule: Specifications are sourced from Huawei Cloud official document dws_01_00018 (updated 2026-07-31). Scripts must be executed via skill action=exec; direct shell execution is prohibited.
pip install openpyxl)Collect the following key information (8 required + 2 optional):
| Category | Survey Item | Description |
|---|---|---|
| Scenario type | Migration / Greenfield | Determines CPU core calculation method |
| Data volume | Total data to warehouse (GB/TB) | Basis for CPU core and storage capacity calculation |
| Daily incremental (optional) | Daily average new data (GB/day) | Storage growth reserve and scale-out cadence; does not change node spec |
| Retention period (optional) | Retention cycle (months) | Growth prediction enabled only when daily incremental is also provided |
| Competitor info | Competitor CPU total, memory ratio | Migration scenario only; matching configuration |
| Source cluster survey (v2.4.0) | MPP cluster scale and utilization (5 groups, 20 questions) | Calibrate matching cores and hot data criteria when migrating or taking over source workload |
| Workload | Compute-intensive or not | Greenfield scenario +30% cores |
| Query characteristics | Many point queries or not | Index space +30%~50% |
| Architecture mode | Coupled / Decoupled | Determines storage calculation method and high watermark |
| Cache strategy | Cost-optimized / Performance-optimized / Hot window N days / Custom hot data volume | Decoupled only (v2.3.0) |
| Deployment region | Target region | Flavor availability |
Source cluster survey checklist: references/source-cluster-survey.md
| Architecture | Applicable Scenario | High Watermark | Cache Strategy |
|---|---|---|---|
| Coupled | <20TB, high performance | 70% | N/A (all data on local SSD) |
| Decoupled | >=20TB or low hot data ratio / fast growth | 80% | Cost-optimized 50% / Performance-optimized 100% / Hot window N days / Custom (v2.3.0) |
Storage calculation rules: references/storage-calculation.md
Full CPU calculation logic: references/cpu-sizing-algorithm.md
Iterate through DWS dedicated flavor catalog (dwsx2/dwsx3/dwsax3 series), satisfying hard constraints (>=16 cores/>=64GB/>=3 nodes), select the combination with minimum compute surplus (nodes + storage). Selection rationale is auto-generated via four-step formula chain: (1) compute derivation -> (2) memory ratio -> (3) concurrency/HA -> (4) storage verification.
Flavor catalog: references/ecs-flavor-catalog.md Selection algorithm: references/single-plan-algorithm.md
Storage capacity (based on current warehouse volume):
Growth reserve (optional, requires both daily incremental + retention period):
Growth calculation and Excel template: references/excel-report-template.md
Generate structured Markdown report + 5-sheet Excel report:
| Sheet | Name | Content |
|---|---|---|
| 1 | Config Recommendation Overview | Single plan summary + detailed spec |
| 2 | Resource and Storage Calculation | CPU derivation + storage capacity calculation process |
| 3 | Selection Decision Rationale | Decision points + candidate flavor comparison table |
| 4 | Capacity Growth and Scale-out Recommendations | Daily incremental x retention period -> scale-out time point |
| 5 | Decoupled OBS Spec | OBS capacity calculation |
Common scenarios: references/sizing-scenarios.md
python scripts/generate_dws_report.py
File naming: DWS_Sizing_Report_<YYYYMMDD>.xlsx
| Parameter | Required/Optional | Description | Default |
|---|---|---|---|
| Scenario type | Required | Migration / Greenfield; determines CPU core calculation method | N/A |
| Total warehouse data | Required | GB/TB; basis for CPU core and storage capacity calculation | N/A |
| Competitor CPU total and memory ratio | Conditional | Migration scenario only; matching configuration; fallback to ceil(data/100GB) when not provided | Uses fallback formula when not provided |
| Source cluster survey | Conditional | Calibrate matching cores and hot data caliber when migrating | N/A |
| Workload | Required | Compute-intensive or not; greenfield compute-intensive x1.3 | Non-compute-intensive |
| Query characteristics | Required | Many point queries or not; index space +30%~50% | Default +30% with annotation |
| Architecture mode | Required | Coupled / Decoupled; determines storage calculation and high watermark | N/A |
| Cache strategy | Conditional | Decoupled only; cost-optimized 50% / performance-optimized 100% / hot window N days / custom hot data volume | Performance-optimized 100% |
| Deployment region | Required | Target region | N/A |
| Daily incremental data | Optional | Daily new data GB/day; for storage growth reserve and scale-out cadence only; does not change node spec | N/A |
| Data retention period | Optional | Retention cycle (months); growth prediction enabled only when daily incremental also provided | N/A |
| Document | Description |
|---|---|
| Acceptance Criteria | Spec output acceptance criteria |
| CPU Sizing Algorithm | CPU core calculation algorithm (migration/greenfield) |
| ECS Flavor Catalog | DWS dedicated flavor catalog (dwsx2/dwsx3/dwsax3 series 1:4/1:8) |
| IAM Policies | IAM permission requirements (no API permissions needed for this planning skill) |
| Single Plan Algorithm | Single-plan minimum-spec selection algorithm and candidate comparison |
| Storage Calculation | Storage capacity calculation (coupled/decoupled, high watermark, index space) |
| Excel Report Template | Excel report template and report_data data structure |
| Sizing Scenarios | Common planning scenarios (Scenario A-F, with daily incremental growth examples) |
| Source Cluster Survey | Source cluster survey checklist (5 groups, 20 items, v2.4.0) |
| Verification Methods | Output verification and validation methods |
scripts/
└── generate_dws_report.py # Excel report generation (5 sheets, single plan + growth analysis)
references/
├── acceptance-criteria.md # Spec output acceptance criteria
├── cpu-sizing-algorithm.md # CPU core calculation algorithm (migration/greenfield)
├── ecs-flavor-catalog.md # DWS dedicated flavor catalog (dwsx2/dwsx3/dwsax3 series 1:4/1:8)
├── excel-report-template.md # Excel report template and report_data data structure
├── iam-policies.md # IAM permission requirements (no API permissions needed)
├── single-plan-algorithm.md # Single-plan minimum-spec selection algorithm and candidate comparison
├── sizing-scenarios.md # Common planning scenarios (Scenario A-F, with daily incremental growth examples)
├── source-cluster-survey.md # Source cluster survey checklist (5 groups, 20 items, v2.4.0)
├── storage-calculation.md # Storage capacity calculation (coupled/decoupled, high watermark, index space)
└── verification-method.md # Output verification and validation methods
python scripts/generate_dws_report.py to generate Excel report; confirm 5 sheets output (Config Recommendation Overview / Resource and Storage Calculation / Selection Decision Rationale / Capacity Growth and Scale-out Recommendations / Decoupled OBS Spec)