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ivanshamaev

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1. ▌
   Mage AI Pipelines · ivanshamaev

   Mage AI data pipelines — block types (data loader/transformer/exporter/sensor/custom), pipeline YAML, hybrid SQL+Python blocks, triggers (schedule/event/API), streaming pipelines, dbt integration, Spark integration, Docker/Kubernetes deployment, io_config.yaml, pipeline variables, callbacks, backfills
   0 installs
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   Sqlmesh · ivanshamaev

   SQLMesh data transformation framework — model kinds (FULL/INCREMENTAL_BY_TIME_RANGE/INCREMENTAL_BY_UNIQUE_KEY/SCD_TYPE_2/VIEW/SEED), plan/apply workflow, virtual environments, state-aware deploys, audits, unit tests, CI/CD, dbt migration
   0 installs
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   Vertica · ivanshamaev

   Use when writing, reviewing, debugging, or optimizing SQL for Vertica — covering DDL (CREATE/ALTER/DROP TABLE, columns, projections, segmentation, partitions), DML (INSERT, UPDATE, DELETE, MERGE, TRUNCATE, COPY), CRUD patterns, and Vertica-specific performance guidance including encoding, segmentation keys, partition pruning, and query optimization.
   0 installs
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   Dbt Core · ivanshamaev

   dbt Core (adapter-agnostic) — project structure, models (SQL/Python), sources and refs, materializations (table/view/incremental/ephemeral), incremental strategies (append/merge/delete+insert), is_incremental() macro, snapshots (SCD Type 2), seeds, tests (generic/singular/severity), Jinja macros, dbt-utils package, node selection syntax (graph operators), hooks, exposures, metrics (MetricFlow), CI/CD (slim CI with state:modified+), dbt_project.yml, profiles.yml, multi-adapter support (Spark/PostgreSQL/ClickHouse/BigQuery)
   0 installs
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   Ray Data · ivanshamaev

   Ray Data distributed data processing — Dataset API, read_parquet/read_csv/read_json/read_delta_sharing, map/filter/flat_map/map_batches, groupby/aggregations, Actors for stateful transforms, Ray remote functions, write_parquet/write_iceberg, streaming execution, GPU batch inference, integration with Spark and Airflow
   0 installs
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   Redpanda · ivanshamaev

   Redpanda Kafka-compatible streaming — cluster setup, topic config, rpk CLI, producer/consumer tuning, tiered storage, Schema Registry, Kafka Connect compatibility, monitoring, Docker/Kubernetes deployment
   0 installs
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   Sqlfluff · ivanshamaev

   SQLFluff SQL linter — .sqlfluff config, dialect selection (ansi/bigquery/clickhouse/duckdb/hive/postgres/snowflake/sparksql/trino), rule sets, templating (Jinja/dbt), fix command, VS Code integration, pre-commit hook, CI/CD GitHub Actions, custom rules, noqa inline suppression
   0 installs
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   Dbt Trino · ivanshamaev

   Use when writing, configuring, or optimizing dbt projects targeting Trino or Starburst — covering profiles.yml setup, all authentication methods, materializations (table/view/incremental/materialized_view/ephemeral), incremental strategies (append/merge/delete+insert), table properties (format/partitioning/sorted_by), on_schema_change, seeds, snapshots, grants, session properties, data modeling patterns (Kimball/staging/intermediate/mart), dbt project structure, tests, and CI/CD.
   0 installs
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   Soda Core · ivanshamaev

   Soda Core data quality — SodaCL checks (row_count, missing, invalid, duplicate, freshness, schema, reference, custom SQL), configuration.yml for PostgreSQL/Spark/ClickHouse/BigQuery, soda scan CLI, Airflow integration, dbt integration, alerting
   0 installs
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    Spark SQL · ivanshamaev

    Use when writing, reviewing, debugging, or optimizing production Spark SQL for Hive/lakehouse/HDFS tables, including CTE-heavy queries, joins, windows, partition pruning, Hive Metastore operations, insert/overwrite safety, query hints, statistics, EXPLAIN plans, AQE, skew, materialization, and SQL performance diagnostics.
    0 installs
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    Dbt Macros · ivanshamaev

    dbt Jinja macros — macro authoring fundamentals, Jinja syntax (blocks/filters/tests), context variables (this/target/adapter/execute), run_query, adapter.dispatch for cross-database macros, generate_schema_name, hooks, custom materializations, dbt-utils patterns
    0 installs
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    Delta Lake · ivanshamaev

    Delta Lake — table DDL (CREATE/PARTITIONED BY/LOCATION/TBLPROPERTIES), DML (INSERT/UPDATE/DELETE/MERGE), MERGE patterns (upsert/SCD2/CDC), schema evolution (mergeSchema/overwriteSchema/ALTER TABLE), OPTIMIZE compaction, Z-ORDER BY data skipping, VACUUM, Time Travel (VERSION AS OF/TIMESTAMP AS OF), RESTORE, DESCRIBE HISTORY, shallow/deep clone, Change Data Feed, streaming read/write, deletion vectors, table properties
    0 installs
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    Aiops Observability Copilot · ivanshamaev

    AIOps observability copilot — natural language to PromQL/LogQL translation, alert explanation in plain English (what fired/why/impact), Grafana dashboard auto-generation from service topology, anomaly narrative generation from metric patterns, on-call context enrichment (related alerts/recent deploys/runbook links), log pattern clustering for noise reduction, SLO status explanation, automated weekly observability health digest
    0 installs
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    Dataops Root Cause Analysis · ivanshamaev

    Root cause analysis for DataOps incidents — 5-Why analysis for pipeline failures, failure taxonomy (infrastructure/data/logic/dependency/config/concurrency), Airflow diagnosis (task state SQL/scheduler heartbeat/DagBag errors), Spark diagnosis (OOM/skew/FetchFailed/serialization), Kafka consumer lag spike RCA, data quality anomaly investigation (volume/freshness/distribution shift), log correlation across components, timeline reconstruction, impact quantification SQL
    0 installs
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    Infra Docker Best Practices · ivanshamaev

    Docker best practices — multi-stage builds (builder/runtime separation), layer cache optimization (dependency install before source copy), minimal base images (distroless/alpine/slim), security hardening (non-root USER, read-only FS, no SUID binaries), .dockerignore patterns, BuildKit secrets for private registries, image vulnerability scanning (Trivy), COPY vs ADD, CMD vs ENTRYPOINT patterns, data engineering Dockerfiles (dbt/Spark/Python ETL)
    0 installs
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    Infra Kafka Platform Review · ivanshamaev

    Kafka production platform review — broker configuration (replication factor/min.insync.replicas/rack awareness/KRaft mode), topic design (partition count formula/compaction/retention), consumer group management (lag monitoring/rebalance tuning/cooperative sticky), producer tuning (acks/idempotence/compression/batching), security (SASL_SSL/ACLs/mTLS), JMX metrics to Prometheus (kafka-exporter/JMX exporter), alert rules (under-replicated partitions/ISR shrink/consumer lag/disk), capacity planning, Strimzi Kubernetes operator
    0 installs
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    Starrocks Aggregation Optimizer · ivanshamaev

    StarRocks aggregation optimization — one-phase vs two-phase aggregation, pre-aggregation pushdown to scan, Aggregate Key table automatic merge, GROUP BY on distribution key (local aggregation), COUNT DISTINCT optimization (multi-phase), HLL/BITMAP approximate aggregation, aggregation spill tuning, EXPLAIN aggregation nodes
    0 installs
18. ▌
    Starrocks Concurrency Optimizer · ivanshamaev

    StarRocks high-concurrency optimization — pipeline_dop tuning for BI workloads, resource groups for workload isolation (short_query type), query queue configuration, FE connection pool, tablet scan parallelism, point query optimization (Primary Key table direct lookup), query cache for repeated dashboard queries, BE thread pool tuning
    0 installs
19. ▌
    Starrocks Data Quality Guardian · ivanshamaev

    StarRocks data quality — freshness queries (MAX(updated_at) vs expected SLA), duplicate detection on Primary Key tables, null anomaly SQL (column-level null rate vs baseline), volume drift detection (day-over-day ratio), cross-table referential integrity checks, data completeness for partitions, StarRocks-specific quality checks (tablet health, compaction lag, replication factor), Python DQ scan class
    0 installs
20. ▌
    Starrocks Lakehouse Integration · ivanshamaev

    StarRocks lakehouse integration — Iceberg/Hive/Delta external catalogs (HMS/Glue/REST), cross-catalog INSERT INTO SELECT, partition filter pushdown verification, external table statistics (ANALYZE on Iceberg), writing back to Iceberg from StarRocks (3.1+), Delta Lake catalog setup, Unity Catalog (3.2+), query federation across StarRocks + Iceberg + Hive in single SQL, cache invalidation (REFRESH EXTERNAL TABLE)
    0 installs
21. ▌
    Dataops Cicd Pipeline Review · ivanshamaev

    DataOps CI/CD pipeline review — pipeline stages for data projects (lint/test/build/scan/deploy), trunk-based vs GitFlow branching, environment promotion (dev→staging→prod), artifact versioning (Docker image tags/dbt manifest), deployment gating (DQ checks/smoke tests/manual approval), rollback strategy, pipeline observability (DORA metrics), reusable workflow patterns, monorepo vs polyrepo CI strategy
    0 installs
22. ▌
    Dataops Postmortem Generator · ivanshamaev

    DataOps blameless postmortem generation — severity matrix (SEV1-4), postmortem Markdown template with timeline/impact/root cause/action items, 3 filled-in examples (Kafka rebalance/dbt incremental data loss/ClickHouse schema mutation), CAPA framework (Corrective/Action/Preventive/Action), impact quantification SQL, stakeholder communication templates, 60-min facilitation guide, postmortem review checklist, Git-based postmortem repository management
    0 installs
23. ▌
    Infra Multi Cloud Governance · ivanshamaev

    Multi-cloud governance — cloud-agnostic data platform patterns, federated identity (OIDC/SAML between AWS/GCP/Azure), Terraform multi-cloud modules, cross-cloud data replication (S3↔GCS/Azure), unified cost management (FinOps Foundation framework), cloud-agnostic observability (OpenTelemetry), policy enforcement (OPA Gatekeeper across clouds), disaster recovery cross-cloud, vendor lock-in avoidance (open formats Iceberg/Parquet), centralized secrets management (HashiCorp Vault)
    0 installs
24. ▌
    Starrocks Admin Storage Balancer · ivanshamaev

    StarRocks storage balancing — tablet distribution across BEs, disk skew detection (SHOW BACKENDS disk usage), cluster_balance analysis (SHOW PROC '/cluster_balance'), balance_load_score_threshold tuning, tablet migration monitoring, BE decommission, adding new BE nodes, storage capacity forecasting, imbalance alerts
    0 installs
25. ▌
    Starrocks Medallion Architecture · ivanshamaev

    StarRocks Medallion (Bronze/Silver/Gold) architecture — Bronze raw ingestion (Duplicate Key), Silver cleansed layer (Primary Key upsert/dedup), Gold aggregated layer (Aggregate Key or MV), incremental transform patterns (INSERT OVERWRITE partition, watermark-based), layer DDL patterns, CDC Bronze landing, dbt-compatible layer design, inter-layer INSERT SELECT pipelines
    0 installs
26. ▌
    Aiops Capacity Planning Agent · ivanshamaev

    AIOps capacity planning agent — predictive resource forecasting (Prophet/linear regression on Prometheus metrics), Kubernetes HPA/VPA right-sizing recommendations, node capacity headroom calculator, Kafka partition and broker capacity model, Spark executor sizing from job history, data lake storage growth forecast (S3/GCS), cluster autoscaler simulation, automatic HPA threshold tuning, cost-per-job attribution, capacity planning report generator
    0 installs
27. ▌
    Dataops Sla Monitoring · ivanshamaev

    Data platform SLA monitoring — freshness SLAs (data available by X:XX), completeness SLAs (row count variance < N%), latency SLAs (pipeline completes within N minutes), SLA breach detection (Prometheus/Soda/SQL), SLA burn rate alerting, SLA reporting dashboards, SLA miss root cause linking, cascading SLA dependencies (upstream delay propagation), SLA definition process, error budget tracking, consumer notification on SLA breach
    0 installs
28. ▌
    Infra Terraform Review · ivanshamaev

    Terraform code review — module structure (main/variables/outputs/modules layout), variable validation blocks, type constraints, sensitive variables, locals vs variables, resource naming conventions, provider version pinning, data sources vs resources, module composition patterns, state management (remote backend S3/GCS), workspace strategy, dependency management (depends_on vs implicit), terraform fmt/validate/tflint checks, DRY with Terragrunt
    0 installs
29. ▌
    Airflow Starrocks Backfill · ivanshamaev

    Airflow + StarRocks backfill patterns — historical partition reprocessing, date range loops with INSERT OVERWRITE, Broker Load replay for S3 partitions, safe backfill with max_active_runs=1, partial backfill resume from checkpoint, backfill idempotency via label strategy, clearing downstream tasks before rerun, parallel partition backfill with concurrency limits
    0 installs
30. ▌
    Airflow Starrocks Pipeline · ivanshamaev

    Airflow + StarRocks pipeline orchestration — MySqlHook for DDL/DML, Broker Load trigger + poll pattern, Stream Load via HTTP operator, Routine Load job lifecycle (pause/resume/stop), sensor for load completion, ANALYZE TABLE post-load, partition-aware DAG templating, Airflow variables for StarRocks connection config, XCom label passing
    0 installs
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    Starrocks Admin Compaction · ivanshamaev

    StarRocks compaction tuning — base compaction vs cumulative compaction, compaction score analysis, write amplification reduction, BE config parameters (compaction_threads/min_cumulative_compaction_num_singleton_deltas/max_compaction_candidate_num), SHOW PROC '/compactions', manual compaction trigger, Primary Key table compaction, rowset management
    0 installs
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    Starrocks Schema Evolution · ivanshamaev

    StarRocks schema evolution — ALTER TABLE ADD/DROP/MODIFY/REORDER COLUMN, column type widening rules, adding columns to Aggregate/Unique/Primary Key tables, schema change types (direct vs linked vs sorted), SHOW ALTER TABLE COLUMN progress, rollback safety, backward-compatible patterns, dbt model evolution, zero-downtime migration checklist
    0 installs
33. ▌
    Trino File Layout Optimization · ivanshamaev

    Trino data file layout optimization for Iceberg — Parquet vs ORC file format selection, target file size tuning (iceberg.target-max-file-size), row group size, Parquet/ORC column encoding choices, Bloom filter indexes, sorted_by for min/max skipping, small file detection via $files metadata table, OPTIMIZE compaction strategies, partition design impact on file count, Z-order equivalent via sorted_by, split sizing and parallelism (iceberg.minimum-assigned-split-weight), write parallelism tuning
    0 installs
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    Starrocks Join Optimization · ivanshamaev

    StarRocks join optimization — broadcast join (small dimension to all BEs), shuffle/hash join (repartition both sides), colocate join (no network transfer, same distribution key), bucket shuffle join, nested loop join (cross join/non-equi), join strategy selection rules, runtime filter effect on joins, join hints, EXPLAIN join strategy verification, skew join handling
    0 installs
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    Starrocks Realtime Modeling · ivanshamaev

    StarRocks real-time data modeling — Primary Key table streaming upserts (Flink/Kafka Routine Load), mutable dimension tables (partial column UPDATE), real-time pre-aggregation with Aggregate Key + streaming inserts, Routine Load for Kafka CDC, real-time materialized view refresh, low-latency BI patterns, latency vs consistency trade-offs
    0 installs
36. ▌
    Trino Resource Group Governance · ivanshamaev

    Trino resource group workload governance — resource-groups.properties configuration (maxQueued/hardConcurrencyLimit/softMemoryLimit/hardCpuLimit/schedulingPolicy/schedulingWeight), hierarchical group trees, selector rules (user/source/queryType/clientTags/regex), multi-tenant tenant isolation patterns, per-user dynamic sub-groups (${USER} template), scheduling policies (fair/weighted_fair/weighted/query_priority), CPU quota periods, database-backed configuration (MySQL/PostgreSQL), JMX monitoring of group utilization
    0 installs
37. ▌
    Dbt Starrocks Semantic Layer · ivanshamaev

    dbt + StarRocks semantic layer — dbt Semantic Layer (MetricFlow) on StarRocks, metric definitions (simple/ratio/cumulative/derived), dimension definitions, saved queries, semantic model DDL, exposures for BI tool documentation, dbt-metricflow query CLI, linking metrics to StarRocks materialized views for performance, business KPI governance patterns
    0 installs
38. ▌
    Starrocks AI Query Autotuner · ivanshamaev

    StarRocks AI query autotuner — autonomous SQL optimization agent workflow (EXPLAIN COSTS → analyze → recommend), materialized view recommendation from slow query log, index recommendation (bitmap/bloom filter), partition pruning diagnosis, join order hints generation, statistics staleness detection and auto-ANALYZE trigger, slow query pattern classification, query rewrite suggestions
    0 installs
39. ▌
    Starrocks Materialized Views · ivanshamaev

    StarRocks materialized views — synchronous MV (rollup/aggregate acceleration), asynchronous MV (CREATE MATERIALIZED VIEW REFRESH ASYNC/MANUAL/SCHEDULED, partition-aware refresh, query rewrite, nested MVs, MV on Iceberg/Hive external tables), SHOW MATERIALIZED VIEWS, ALTER/REFRESH/DROP MV, transparent query rewrite via EXPLAIN, use_mv hint
    0 installs
40. ▌
    Starrocks Realtime Analytics · ivanshamaev

    StarRocks real-time analytics — Kafka → Routine Load → Primary Key table for sub-second freshness, low-latency BI query patterns, real-time dashboard design (materialized view for pre-aggregation), metric store patterns, window-based freshness for streaming dashboards, colocate join for real-time multi-table queries, resource group isolation for OLAP vs ingestion
    0 installs
41. ▌
    Starrocks Routine Load Kafka · ivanshamaev

    StarRocks Routine Load for Kafka — CREATE ROUTINE LOAD DDL (all PROPERTIES/KAFKA clause parameters), JSON/CSV/Avro format config, desired_concurrent_number tuning, SHOW ROUTINE LOAD columns, PAUSE/RESUME/ALTER/STOP, consumer lag monitoring, error log analysis, exactly-once semantics, Schema Registry for Avro, Kafka SASL/SSL config, idempotent upsert to Primary Key table
    0 installs
42. ▌
    De Architecture Decision · ivanshamaev

    DE architecture decision records (ADR) — ADR template, trade-off analysis framework, technology evaluation criteria, common DE architecture decisions (storage format, orchestrator, streaming vs batch, lakehouse vs warehouse), decision reversibility, stakeholder communication
    0 installs
43. ▌
    De Root Cause Analysis · ivanshamaev

    DE pipeline root cause analysis — failure taxonomy, lineage tracing, upstream/downstream impact, log analysis patterns, Airflow/Spark/dbt failure diagnosis, data quality anomaly RCA, 5-Whys template, incident timeline reconstruction, runbook-style investigation checklists
    0 installs
44. ▌
    Duckdb · ivanshamaev

    DuckDB in-process OLAP analytics — reading Parquet/CSV/JSON/Iceberg/Delta from S3/local, SQL (window functions, PIVOT, ASOF join, QUALIFY), Python API (duckdb.connect, fetchdf, register, UDFs), extensions (httpfs/iceberg/delta/postgres), performance tuning, COPY TO, persistent DB
    0 installs
45. ▌
    Airbyte · ivanshamaev

    Airbyte ELT — source/destination connectors, sync modes (Full Refresh Overwrite/Append, Incremental Append/Deduped), cursor fields, primary keys, catalog/streams, deployment (abctl, Kubernetes Helm, Airbyte Cloud), Connector Builder, Python CDK (HttpStream, IncrementalMixin), normalization (dbt-based, _airbyte_raw_ tables), Airbyte API, Terraform provider, schema evolution, monitoring, Airflow AirbyteTriggerSyncOperator integration
    0 installs
46. ▌
    Starrocks Memory Tuning · ivanshamaev

    StarRocks memory tuning — BE memory architecture (mem_limit, query pool, load pool, compaction pool, metadata cache), query memory limits (query_mem_limit session var), memory spill to disk (spill_mode), OOM analysis (be.out log), mem_tracker hierarchy, FE heap tuning (JAVA_OPTS), Primary Key table persistent index memory, jemalloc tuning
    0 installs
47. ▌
    Trino Airflow Orchestration · ivanshamaev

    Airflow orchestration for Trino pipelines — TrinoOperator and TrinoHook usage, trino_conn_id connection setup, idempotent DAG patterns (INSERT INTO / MERGE with deterministic run_ids), partition-aware scheduling with Airflow logical_date, sensor patterns (TrinoCheckOperator), SLA monitoring, retry configuration for Trino queries, incremental load orchestration, dbt + Trino Airflow integration (BashOperator/DbtRunOperator), metadata-driven DAG generation
    0 installs
48. ▌
    Trino Dbt Query Performance · ivanshamaev

    Optimizing dbt-generated SQL performance on Trino — ephemeral vs view vs table materialization trade-offs, CTE explosion patterns, partition-aware incremental filters (bounded watermarks), MERGE vs delete+insert strategy selection, avoiding full-refresh anti-patterns, query hints in dbt SQL (BROADCAST hint), dbt thread tuning, session_properties for dbt runs, ANALYZE post-hooks, incremental model design patterns for Iceberg, avoiding small file proliferation from frequent incremental runs
    0 installs
49. ▌
    Trino Self Healing Platform · ivanshamaev

    Autonomous self-healing Trino platform — Python watchdog agents for automatic worker restart detection, hung query killer, OOM-killed query resubmission, Iceberg compaction auto-trigger on small-file detection, stale statistics auto-ANALYZE, cluster memory pressure relief (kill low-priority queries), anomaly detection on query latency (Z-score), Claude-based RCA generation for incidents, Prometheus AlertManager webhook integration, Airflow self-healing sensor
    0 installs
50. ▌
    Starrocks Admin Security · ivanshamaev

    StarRocks security and RBAC — CREATE USER/ROLE, GRANT/REVOKE privileges (catalog/database/table/view/MV/function/resource group level), built-in roles (cluster_admin/db_admin/user_admin/public), LDAP/LDAP group auth, row-level security policies, column masking, SSL/TLS, audit log, privilege inheritance, security best practices
    0 installs
51. ▌
    Trino Iceberg Best Practices · ivanshamaev

    Production Apache Iceberg best practices with Trino — hidden partitioning (day/month/year/hour/bucket/truncate transforms), partition evolution, sorted tables, file compaction (optimize/expire_snapshots/remove_orphan_files), snapshot management, metadata tables ($snapshots/$files/$partitions/$history), schema evolution, time travel queries, MERGE/UPDATE/DELETE DML, ANALYZE for CBO, Iceberg catalog types (HMS/Glue/REST/Nessie), small file prevention, Bloom filters
    0 installs
52. ▌
    Trino Observability Platform · ivanshamaev

    Trino observability and monitoring platform — JMX Prometheus exporter configuration (running queries/failed queries/OOM kills/execution latency P50/P90/P99/memory pool metrics), Grafana dashboard panels, OpenTelemetry trace propagation, query-level event listener for structured logging, Prometheus alert rules (worker loss/queue depth/OOM/failure rate/p99 latency), log aggregation patterns, query history analysis via REST API, slow query detection SQL
    0 installs
53. ▌
    Dbt Starrocks Performance · ivanshamaev

    dbt + StarRocks performance tuning — model DAG optimization (fan-in/fan-out), incremental merge window sizing, partition-aware incremental filters, avoiding full table rebuilds, query plan hints in dbt SQL (LEADING/JOIN hints), materialized view as dbt model target, concurrent model execution with threads, pre/post hooks for ANALYZE TABLE, dbt run selectors to minimize rebuilt models
    0 installs
54. ▌
    Starrocks AI Incident Rca · ivanshamaev

    StarRocks AI incident RCA — autonomous root cause analysis agent for FE/BE failures, memory spike diagnosis (BE heap/process memory), Routine Load pause RCA (ErrorLogUrls + error patterns), Kafka consumer lag spike analysis, compaction backlog detection, tablet replication failures, OOM kill patterns, query timeout clusters, FE GC pressure detection, structured incident report generation
    0 installs
55. ▌
    Starrocks Ddl Table Types · ivanshamaev

    StarRocks table types — Duplicate Key (append-only log/event), Aggregate Key (pre-aggregation metrics), Unique Key (upsert dedup), Primary Key (full DML upsert/delete, MVCC), CREATE TABLE DDL, key column selection, aggregate functions (SUM/MAX/MIN/REPLACE/HLL_UNION/BITMAP_UNION), when to use each type, storage engine differences
    0 installs
56. ▌
    Starrocks Files Ingestion · ivanshamaev

    StarRocks file ingestion — FILES() table function (SELECT/INSERT from S3/HDFS Parquet/ORC/CSV without CREATE TABLE), Iceberg external catalog (HMS/Glue/REST), CREATE EXTERNAL CATALOG, cross-catalog INSERT INTO SELECT, schema auto-detection, partition filter pushdown on external tables, SHOW CREATE CATALOG, external table DDL patterns
    0 installs
57. ▌
    Starrocks Query Optimizer · ivanshamaev

    StarRocks query optimization — vectorized execution engine, pipeline execution model, runtime filters (bloom/in/min-max), predicate pushdown, partition pruning, sort merge optimization, query hints (SET_VAR/JOIN hints), session variables for optimizer control, CBO statistics (ANALYZE TABLE/AUTO ANALYZE), query cache, pipeline parallelism tuning
    0 installs
58. ▌
    Trino Memory And Spill Tuning · ivanshamaev

    Trino memory management and spill-to-disk tuning — query.max-memory/query.max-total-memory/query.max-memory-per-node properties, memory.heap-headroom-per-node, JVM heap sizing (80% of RAM), spill-enabled/spiller-spill-path/spill-compression-codec configuration, exchange buffer tuning, OOM kill diagnosis, memory pool sizing, fault-tolerant execution exchange manager (S3/filesystem), session-level memory overrides, memory-intensive operator patterns (HashJoin/Sort/Window/GroupBy)
    0 installs
59. ▌
    Trino Security And Governance · ivanshamaev

    Trino security hardening and data governance — TLS/HTTPS setup, internal-communication shared secret, authentication (LDAP/OAuth2/JWT), file-based access control (catalog/schema/table/column rules, column masking, row-level filtering, query kill permissions), OPA integration, Ranger for dynamic row-filter and column-mask, catalog isolation by domain, user group mapping, impersonation rules, audit logging via event listener, password file authentication for development
    0 installs