MO-DIAG Interactive Diagnostic Tool Guide ========================================== This guide covers the MO-DIAG interactive diagnostic tool, a powerful command-line interface for diagnosing and inspecting MatrixOne database objects, especially secondary indexes and vector indexes. Overview -------- MO-DIAG (MatrixOne Diagnostic Tool) provides: * **Index Inspection**: View and analyze all types of indexes (IVF, HNSW, Fulltext, and regular) * **Health Monitoring**: Check index health across all tables in a database * **CDC Health Checks**: Evaluate CDC task status, errors, and watermark lag * **CDC Task Management**: Guided creation, inspection, and safe deletion workflows * **Row Count Verification**: Verify consistency between main tables and index tables * **IVF Status Monitoring**: Monitor IVF vector index centroid distribution and balance * **Table Statistics**: Detailed table and index statistics using metadata scan * **Table Flushing**: Flush tables and their indexes to disk (requires sys privileges) * **Interactive Shell**: Tab completion, command history, and intuitive interface Features ~~~~~~~~ * 🎯 **Interactive Mode**: Full-featured shell with tab completion and history * 🚀 **Non-Interactive Mode**: Execute single commands for scripting (including ``mo-diag cdc`` helpers) * 📊 **Comprehensive Diagnostics**: Inspect all aspects of tables and indexes * 🩺 **CDC Monitoring**: Run CDC health checks to surface lagging or errored tasks * 🔍 **Smart Completion**: Auto-complete table names, database names, and commands * 📝 **Command History**: Browse and search command history with arrows and Ctrl+R * 🎨 **Colored Output**: Easy-to-read colored output for better visibility Getting Started --------------- Installation ~~~~~~~~~~~~ The MO-DIAG tool is included in the MatrixOne Python SDK: .. code-block:: bash pip install matrixone-python-sdk Basic Usage ~~~~~~~~~~~ **Interactive Mode:** .. code-block:: bash # Start with default connection python mo_diag.py # Start with specific connection parameters python mo_diag.py --host localhost --port 6001 --database test # Start with custom logging level python mo_diag.py --host localhost --port 6001 --log-level DEBUG **Non-Interactive Mode:** .. code-block:: bash # Execute a single command and exit python mo_diag.py -d test -c "show_ivf_status" python mo_diag.py -d test -c "show_table_stats my_table -a" python mo_diag.py -d test -c "sql SELECT COUNT(*) FROM my_table" **If installed via pip:** .. code-block:: bash # Interactive mode mo-diag --host localhost --port 6001 --database test # Non-interactive mode mo-diag -d test -c "show_ivf_status" Connection Management --------------------- connect ~~~~~~~ Connect to a MatrixOne database. .. code-block:: text Usage: connect [database] Example: connect localhost 6001 root 111 test connect 192.168.1.100 6001 admin secret production_db use ~~~ Switch to a different database. .. code-block:: text Usage: use Example: use test use production_db databases ~~~~~~~~~ List all available databases. .. code-block:: text Usage: databases Example: databases tables ~~~~~~ List all tables in the current database. .. code-block:: text Usage: tables [database] Example: tables tables test Index Inspection Commands -------------------------- show_indexes ~~~~~~~~~~~~ Show all secondary indexes for a table, including IVF, HNSW, Fulltext, and regular indexes. Uses vertical output format (like MySQL \\G) for easy reading. .. code-block:: text Usage: show_indexes [database] Example: show_indexes my_vector_table show_indexes my_vector_table test **Output includes:** * Index name and algorithm (IVF, HNSW, Fulltext, or regular) * Table type (metadata, centroids, entries) * Physical table name * Indexed columns * Statistics (objects, rows, compressed size, original size) **Example output:** .. code-block:: text 📊 Secondary Indexes for 'test.ivf_health_demo_docs' *************************** 1. row *************************** Index Name: idx_embedding_ivf_v2 Algorithm: ivfflat Table Type: metadata Physical Table: __mo_index_secondary_0199e725-0a7a-77b8-b689-ccdd0a33f581 Columns: embedding Statistics: - Objects: 1 - Rows: 7 - Compressed Size: 940 B - Original Size: 1.98 KB *************************** 2. row *************************** Index Name: idx_embedding_ivf_v2 Algorithm: ivfflat Table Type: centroids Physical Table: __mo_index_secondary_0199e725-0a7b-706e-8f0a-a50edc3621a1 Columns: embedding Statistics: - Objects: 1 - Rows: 17 - Compressed Size: 3.09 KB - Original Size: 6.83 KB *************************** 3. row *************************** Index Name: idx_embedding_ivf_v2 Algorithm: ivfflat Table Type: entries Physical Table: __mo_index_secondary_0199e725-0a7c-77f4-8d0b-48fd8258098a Columns: embedding Statistics: - Objects: 1 - Rows: 1,000 - Compressed Size: 156.34 KB - Original Size: 176.07 KB Total: 3 index tables (1 ivfflat with 3 physical tables) **Output解析:** IVF索引有3个物理表： * **metadata**: 存储索引元数据（7行） * **centroids**: 存储质心向量（17个质心） * **entries**: 存储向量条目（1,000个向量） show_all_indexes ~~~~~~~~~~~~~~~~ Show index health report for all tables with secondary indexes in a database. This command performs diagnostic checks including: * Row count consistency between main table and index tables * Vector index building status (IVF/HNSW) * Index type distribution * Problem detection .. code-block:: text Usage: show_all_indexes [database] Example: show_all_indexes show_all_indexes test **Output includes:** * **Healthy tables**: Tables with consistent indexes * **Attention needed**: Tables with issues (mismatches, incomplete builds) * Summary statistics **Example output:** .. code-block:: text 📊 Index Health Report for Database 'test': ======================================================================================================================== ✓ HEALTHY (3 tables) ------------------------------------------------------------------------------------------------------------------------ Table Name | Indexes | Row Count | Notes ------------------------------------------------------------------------------------------------------------------------ cms_all_content_chunk_info | 3 | ✓ 32,712 rows | - demo_mixed_indexes | 4 | ✓ 20 rows | - ivf_health_demo_docs | 1 | 300 rows | IVF: 17 centroids, 300 vectors ======================================================================================================================== Summary: ✓ 3 healthy tables Total: 3 tables with indexes 💡 Tip: Use 'verify_counts ' or 'show_ivf_status' for detailed diagnostics **Output解析:** * **HEALTHY**: 所有索引表行数与主表一致 * **Row Count**: 显示主表行数，带 ✓ 表示已验证 * **Notes**: 对于IVF索引显示质心数和向量数 * 如果有索引不一致会显示在 "ATTENTION NEEDED" 区域 verify_counts ~~~~~~~~~~~~~ Verify row counts between main table and all its index tables. This is critical for ensuring index consistency, especially after data modifications. .. code-block:: text Usage: verify_counts [database] Example: verify_counts my_table verify_counts my_table test **Output shows:** * Main table row count * Each index table row count * Consistency status (✓ or ❌) **Example output:** .. code-block:: text 📊 Row Count Verification for 'test.users' Main table: 10,000 rows Index: idx_email __mo_index_secondary_018e1234...: 10,000 rows ✓ Index: idx_username __mo_index_secondary_018e5678...: 10,000 rows ✓ ✅ All index tables have consistent row counts! Vector Index Commands --------------------- show_ivf_status ~~~~~~~~~~~~~~~ Show IVF index centroids building status and distribution. This is essential for monitoring IVF vector index health and balance. .. code-block:: text Usage: show_ivf_status [database] - Show compact summary show_ivf_status [database] -v - Show detailed view show_ivf_status [database] -t table - Filter by table name Example: show_ivf_status show_ivf_status test -v show_ivf_status test -t documents **Compact view shows:** * Table and index names * Number of centroids and vectors * Balance ratio (max/min centroid size) * Status (active, empty, or error) **Detailed view (-v) shows:** * Physical table names for each index * Centroid distribution statistics * Top 10 centroids by vector count * Load balance metrics **Example compact output:** .. code-block:: text 📊 IVF Index Status in 'test': Table | Index | Column | Centroids | Vectors | Balance | Status documents | idx_embedding | embedding | 100 | 10,000 | 2.15 | ✓ active images | idx_features | features | 50 | 5,000 | 1.85 | ✓ active Total: 2 IVF indexes Tip: Use 'show_ivf_status test -v' for detailed view with top centroids **Example detailed output:** .. code-block:: text Table: documents | Index: idx_embedding | Column: embedding Physical Tables: - metadata : __mo_index_secondary_018e1234_meta - centroids : __mo_index_secondary_018e1234_centroids - entries : __mo_index_secondary_018e1234_entries Centroid Distribution: Total Centroids: 100 Total Vectors: 10,000 Min/Avg/Max: 80 / 100.0 / 172 Load Balance: 2.15x Top Centroids (by vector count): 1. Centroid 42: 172 vectors (version 1) 2. Centroid 18: 165 vectors (version 1) 3. Centroid 67: 158 vectors (version 1) ... CDC Monitoring Commands ----------------------- cdc_health ~~~~~~~~~~ Run CDC task health diagnostics to spot errors, stuck tasks, and delayed watermarks. .. code-block:: text Usage: cdc_health [threshold_minutes] Example: cdc_health cdc_health 5 **What it checks:** * Tasks whose `err_msg` field is populated * Running tasks whose tables report per-table errors * Tables whose watermarks lag beyond the configured threshold (default 10 minutes) **Sample output:** .. code-block:: text 📈 CDC Health Overview Threshold for watermark lag: 10.0 minute(s) Evaluated CDC tasks: 3 No CDC tasks currently report errors. Running tasks with per-table errors (1): • nightly_sync (state: running) Tables lagging beyond threshold (2): • nightly_sync.analytics.orders (watermark: 2025-11-07 15:02:10) • nightly_sync.analytics.payments (watermark: 2025-11-07 14:55:42) Healthy tasks (no reported issues): 2 CDC Task Management ------------------- cdc_tasks ~~~~~~~~~ List CDC tasks with a concise summary (state, sink type, mapping preview) and optional detail output. .. code-block:: text Usage: cdc_tasks [--details] Example: cdc_tasks cdc_tasks --details With ``--details`` the command includes connection URIs, task options, and checkpoint metadata for each task. cdc_task ~~~~~~~~ Inspect or control an individual CDC task. Watermarks are displayed with human friendly timestamps (UTC) and delay calculations. .. code-block:: text Usage: cdc_task [--details] [--no-watermarks] [--watermarks-only] [--table=] [--threshold=] [--strict] [--pause|--resume|--restart] Example: cdc_task nightly_sync --details cdc_task nightly_sync --threshold=5m --strict cdc_task nightly_sync --pause ``--threshold`` accepts values such as ``30s``, ``5m`` or ``1h``. ``--strict`` is a shorthand for zero tolerance. cdc_create ~~~~~~~~~~ Launch the interactive wizard to create a CDC task. The flow now prints a JSON preview of the final configuration and asks for confirmation before submitting ``CREATE CDC``. .. code-block:: text Usage: cdc_create [--database-level|--table-level] For table-level replication you will be prompted for one or more table mappings in ``source_db.table[:sink_db.table]`` form. cdc_drop ~~~~~~~~ Drop a CDC task. Two confirmation prompts guard against accidental removal; use ``--force`` in scripted scenarios to skip prompts. .. code-block:: text Usage: cdc_drop [--force] Non-interactive automation ~~~~~~~~~~~~~~~~~~~~~~~~~~ The ``mo-diag`` entry point mirrors the interactive commands through ``mo-diag cdc``. This is ideal for automation pipelines: .. code-block:: bash mo-diag cdc show # Summary of all tasks (same as cdc_tasks) mo-diag cdc show nightly_sync --details --threshold=5m mo-diag cdc create --table-level mo-diag cdc drop nightly_sync --force All validations and previews are shared with the interactive counterparts because both routes reuse the same CDC helpers. Table Statistics Commands ------------------------- show_table_stats ~~~~~~~~~~~~~~~~ Show table statistics using metadata scan interface. This provides comprehensive statistics for tables, including tombstone and index data. .. code-block:: text Usage: show_table_stats
[database] - Show table stats summary show_table_stats
[database] -t - Include tombstone stats show_table_stats
[database] -i idx1,idx2 - Include specific index stats show_table_stats
[database] -a - Include all (tombstone + all indexes) show_table_stats
[database] -d - Show detailed object list Example: show_table_stats documents show_table_stats documents test -t show_table_stats documents test -i idx_embedding,idx_title show_table_stats documents test -a show_table_stats documents test -a -d **Brief view (default):** Shows aggregated statistics per component (table, tombstone, indexes). .. code-block:: text 📊 Table Statistics for 'test.ivf_health_demo_docs': ======================================================================================================================== Component | Objects | Rows | Null Count | Original Size | Compressed Size ------------------------------------------------------------------------------------------------------------------------ ivf_health_demo_docs | 1 | 1,200 | 0 | 704.12 KB | 624.94 KB ======================================================================================================================== **With -a flag (all indexes):** .. code-block:: text 📊 Table Statistics for 'test.ivf_health_demo_docs': ======================================================================================================================== Component | Objects | Rows | Null Count | Original Size | Compressed Size ------------------------------------------------------------------------------------------------------------------------ ivf_health_demo_docs | 1 | 1,200 | 0 | 704.12 KB | 624.94 KB └─ index: idx_embedding_ivf_v2 └─ (metadata) | 1 | 7 | 0 | 1.98 KB | 940 B └─ (centroids) | 1 | 17 | 0 | 6.83 KB | 3.09 KB └─ (entries) | 1 | 1,200 | 0 | 696.11 KB | 626.37 KB ======================================================================================================================== **Output解析:** * 主表显示总体统计信息 * IVF索引的3个物理表分别显示统计信息 * Objects: 对象数（segment数） * Rows: 行数 * Original Size: 原始大小 * Compressed Size: 压缩后大小 **Detailed view (-d):** Shows individual object statistics. .. code-block:: text 📊 Detailed Table Statistics for 'test.ivf_health_demo_docs': ====================================================================================================================================================== Table: ivf_health_demo_docs Objects: 1 | Rows: 1,000 | Null: 0 | Original: 176.03 KB | Compressed: 156.24 KB Objects: Object Name | Rows | Null Cnt | Original Size | Compressed Size ---------------------------------------------------------------------------------------------------------------------------------------------------- 0199e729-642e-71e0-b338-67c4980ee294_00000 | 1000 | 0 | 176.03 KB | 156.24 KB **Output解析:** * 显示表的总体统计 * 列出每个对象（segment）的详细信息 * Object Name: 对象的唯一标识符 * Rows/Null Cnt/Sizes: 该对象的统计信息 **Hierarchical view (-a -d):** Shows table → indexes → physical tables → objects in a tree structure. .. code-block:: text 📊 Detailed Table Statistics for 'test.ivf_health_demo_docs': ====================================================================================================================================================== Table: ivf_health_demo_docs Objects: 1 | Rows: 1,000 | Null: 0 | Original: 176.03 KB | Compressed: 156.24 KB Objects: Object Name | Rows | Null Cnt | Original Size | Compressed Size ---------------------------------------------------------------------------------------------------------------------------------------------------- 0199e729-642e-71e0-b338-67c4980ee294_00000 | 1000 | 0 | 176.03 KB | 156.24 KB Index: idx_embedding_ivf_v2 └─ (metadata): __mo_index_secondary_0199e725-0a7a-77b8-b689-ccdd0a33f581:272851 Objects: 1 | Rows: 7 | Null: 0 | Original: 1.98 KB | Compressed: 940 B Objects: Object Name | Rows | Null Cnt | Original Size | Compressed Size ---------------------------------------------------------------------------------------------------------------------------------------------------- 0199e729-642a-7d36-ac37-0ae17325f7ec_00000 | 7 | 0 | 1.98 KB | 940 B └─ (centroids): __mo_index_secondary_0199e725-0a7b-706e-8f0a-a50edc3621a1:272852 Objects: 1 | Rows: 17 | Null: 0 | Original: 6.83 KB | Compressed: 3.09 KB Objects: Object Name | Rows | Null Cnt | Original Size | Compressed Size ---------------------------------------------------------------------------------------------------------------------------------------------------- 0199e729-6431-794d-9c13-d10f2e4a59e7_00000 | 17 | 0 | 6.83 KB | 3.09 KB └─ (entries): __mo_index_secondary_0199e725-0a7c-77f4-8d0b-48fd8258098a:272853 Objects: 1 | Rows: 1,000 | Null: 0 | Original: 696.11 KB | Compressed: 626.37 KB Objects: Object Name | Rows | Null Cnt | Original Size | Compressed Size ---------------------------------------------------------------------------------------------------------------------------------------------------- 0199e729-6438-7db1-bcb6-7b74c59b0aee_00000 | 1000 | 0 | 696.11 KB | 626.37 KB **Output解析:** * **层次结构**: 主表 → 索引 → 物理表 → 对象 * **IVF索引的3个物理表**: metadata, centroids, entries * **物理表名格式**: ``table_name:table_id`` * **Data vs Tombstone**: 如果使用 ``-t`` 参数，会显示 Data 和 Tombstone 两部分 * **用途**: 用于深度分析表和索引的存储结构，定位具体对象 Database Operations ------------------- flush_table ~~~~~~~~~~~ Flush table and all its secondary index tables to disk. **⚠️ Requires sys user privileges.** .. code-block:: text Usage: flush_table
[database] Example: flush_table documents flush_table documents test **Note:** This command will: 1. Flush the main table 2. Automatically discover all index tables (IVF, HNSW, Fulltext, regular) 3. Flush each index table 4. Report success/failure for each operation **Example output:** .. code-block:: text 🔄 Flushing table: test.ivf_health_demo_docs ✓ Main table flushed: ivf_health_demo_docs 📋 Found 3 index physical tables Index: idx_embedding_ivf_v2 ✓ metadata: __mo_index_secondary_0199e725-0a7a-77b8-b689-ccdd0a33f581 ✓ centroids: __mo_index_secondary_0199e725-0a7b-706e-8f0a-a50edc3621a1 ✓ entries: __mo_index_secondary_0199e725-0a7c-77f4-8d0b-48fd8258098a 📊 Summary: Main table: ✓ flushed Index tables: 3/3 flushed successfully **Output解析:** * **主表 flush**: 首先 flush 主表 * **索引表发现**: 自动发现所有索引物理表 * **IVF 索引**: 对于 IVF 索引，会 flush 3个物理表（metadata, centroids, entries） * **普通索引**: 对于普通索引，flush 单个物理表 * **成功率**: 显示成功 flush 的表数量 **注意事项:** * 需要 sys 用户权限 * 对于包含多个索引的表，flush 可能需要较长时间 * 建议在低峰期执行 flush 操作 sql ~~~ Execute arbitrary SQL queries. .. code-block:: text Usage: sql Example: sql SELECT COUNT(*) FROM documents sql SHOW CREATE TABLE documents sql SELECT * FROM documents LIMIT 10 Utility Commands ---------------- history ~~~~~~~ Show command history. .. code-block:: text Usage: history [n] Example: history # Show all history history 10 # Show last 10 commands help ~~~~ Show help information for commands. .. code-block:: text Usage: help [command] Example: help # Show all commands help show_indexes # Show help for show_indexes help show_ivf_status # Show help for show_ivf_status exit / quit ~~~~~~~~~~~ Exit the interactive tool. .. code-block:: text Usage: exit quit Ctrl+D (EOF) Real-World Examples ------------------- Monitoring Vector Index Health ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. code-block:: python # Start mo_diag python mo_diag.py --database test # 1. Check overall index health MO-DIAG[test]> show_all_indexes # 2. Inspect specific table indexes MO-DIAG[test]> show_indexes documents # 3. Check IVF index status and balance MO-DIAG[test]> show_ivf_status -v # 4. Get detailed statistics MO-DIAG[test]> show_table_stats documents -a Diagnosing Index Issues ~~~~~~~~~~~~~~~~~~~~~~~ .. code-block:: python # 1. List all tables MO-DIAG[test]> tables # 2. Check for row count mismatches MO-DIAG[test]> verify_counts my_table # 3. If mismatch found, check index details MO-DIAG[test]> show_indexes my_table # 4. Check table statistics to identify issues MO-DIAG[test]> show_table_stats my_table -a -d Monitoring IVF Index Balance ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. code-block:: python # 1. Check IVF status across all tables MO-DIAG[test]> show_ivf_status # 2. Get detailed view for specific table MO-DIAG[test]> show_ivf_status -t documents -v # 3. If balance ratio is high (>2.5), consider rebuilding # Check current statistics before rebuild MO-DIAG[test]> show_table_stats documents -i idx_embedding -d Flushing Tables Before Backup ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. code-block:: python # Connect with sys user (required for flush operations) python mo_diag.py --user sys#root --password 111 --database test # 1. List all tables MO-DIAG[test]> tables # 2. Flush critical tables MO-DIAG[test]> flush_table documents MO-DIAG[test]> flush_table users MO-DIAG[test]> flush_table orders # 3. Verify flush succeeded by checking statistics MO-DIAG[test]> show_table_stats documents -a Scripting with Non-Interactive Mode ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ .. code-block:: bash #!/bin/bash # Daily health check script # Check overall health python mo_diag.py -d production -c "show_all_indexes" > health_report.txt # Check IVF index status python mo_diag.py -d production -c "show_ivf_status" >> health_report.txt # Get statistics for critical tables for table in documents users orders; do echo "=== $table ===" >> health_report.txt python mo_diag.py -d production -c "show_table_stats $table -a" >> health_report.txt done # Email report mail -s "Daily DB Health Report" admin@example.com < health_report.txt Best Practices -------------- Index Health Monitoring ~~~~~~~~~~~~~~~~~~~~~~~ 1. **Regular Checks**: Run ``show_all_indexes`` daily to catch issues early 2. **IVF Balance**: Monitor IVF balance ratio; rebuild if > 2.5x 3. **Row Count Verification**: Verify counts after large data operations 4. **Statistics Review**: Check table statistics weekly for growth trends Vector Index Optimization ~~~~~~~~~~~~~~~~~~~~~~~~~~ 1. **Monitor Centroids**: Use ``show_ivf_status -v`` to check centroid distribution 2. **Balance Ratio**: Keep balance ratio below 2.5x for optimal performance 3. **Regular Rebuilds**: Rebuild IVF indexes periodically if data distribution changes 4. **Size Tracking**: Monitor index sizes with ``show_table_stats -a`` Table Flushing ~~~~~~~~~~~~~~ 1. **Sys Privileges**: Always connect with sys account for flush operations 2. **Before Backups**: Flush critical tables before taking backups 3. **After Bulk Loads**: Flush after large data inserts/updates 4. **Verify Success**: Check table statistics after flushing Troubleshooting --------------- Connection Issues ~~~~~~~~~~~~~~~~~ **Problem:** Cannot connect to database **Solution:** .. code-block:: text # Check connection parameters python mo_diag.py --host localhost --port 6001 --user root --password 111 --log-level DEBUG # Or connect manually within the tool MO-DIAG> connect localhost 6001 root 111 test Permission Errors ~~~~~~~~~~~~~~~~~ **Problem:** "Permission denied" when flushing tables **Solution:** Connect with sys account: .. code-block:: bash # Method 1: Use sys#root format python mo_diag.py --user sys#root --password 111 --database test # Method 2: Within the tool MO-DIAG> connect localhost 6001 sys#root 111 test No IVF Statistics ~~~~~~~~~~~~~~~~~ **Problem:** IVF index shows "no stats available" **Solution:** 1. Check if index is built: ``show_indexes
`` 2. Verify there's data in the table: ``sql SELECT COUNT(*) FROM
`` 3. Wait for index building to complete (for new indexes) 4. Check index health: ``show_all_indexes`` Row Count Mismatches ~~~~~~~~~~~~~~~~~~~~ **Problem:** ``verify_counts`` shows mismatches **Solution:** 1. Check if there are ongoing transactions 2. Flush the table: ``flush_table
`` 3. Re-verify: ``verify_counts
`` 4. If persists, inspect index details: ``show_indexes
`` Command Reference Summary ------------------------- **Connection:** * ``connect [database]`` - Connect to database * ``use `` - Switch database * ``databases`` - List databases * ``tables [database]`` - List tables **Index Inspection:** * ``show_indexes
[database]`` - Show all indexes for a table * ``show_all_indexes [database]`` - Show health report for all tables * ``verify_counts
[database]`` - Verify row count consistency * ``show_ivf_status [database] [-v] [-t table]`` - Show IVF index status **Statistics:** * ``show_table_stats
[database] [-t] [-i idx] [-a] [-d]`` - Show table statistics **Operations:** * ``flush_table
[database]`` - Flush table and indexes (requires sys) * ``sql `` - Execute SQL query **Utility:** * ``history [n]`` - Show command history * ``help [command]`` - Show help * ``exit / quit`` - Exit tool Command-Line Options -------------------- .. code-block:: bash python mo_diag.py [options] Options: --host HOST Database host (default: localhost) --port PORT Database port (default: 6001) --user USER Database user (default: root) --password PASSWORD Database password (default: 111) --database DATABASE, -d DATABASE Database name (optional) --log-level LEVEL Logging level: DEBUG, INFO, WARNING, ERROR, CRITICAL (default: ERROR) --command COMMAND, -c COMMAND Execute a single command and exit (non-interactive mode) Programmatic Usage ------------------ You can also use the MO-DIAG tool programmatically in your Python scripts: .. code-block:: python from matrixone import Client from matrixone.cli_tools import MatrixOneCLI, start_interactive_tool # Method 1: Start interactive tool start_interactive_tool( host='localhost', port=6001, user='root', password='111', database='test', log_level='ERROR' ) # Method 2: Use CLI programmatically client = Client() client.connect(host='localhost', port=6001, user='root', password='111', database='test') cli = MatrixOneCLI(client) # Execute commands cli.onecmd("show_all_indexes") cli.onecmd("show_ivf_status -v") cli.onecmd("show_table_stats documents -a") # Clean up client.disconnect() For more information, see the :doc:`api/client` and :doc:`vector_guide`.