Gleam Lab · Blog Archive
Blog Page 25
Technical exploration and engineering notes, 655 articles in total.
Big Data 178 - Elasticsearch 7.3 Java Practice: Index and Document CRUD
This article details the complete flow for index and document CRUD operations using Elasticsearch 7.3.0 and RestHighLevelClient.
Big Data 175 - Elasticsearch Term Queries and Bool Combination Practice
This article demonstrates Elasticsearch term-level queries including term, terms, range, exists, prefix, regexp, fuzzy, ids queries, and bool compound queries.
Big Data 176 - Elasticsearch Filter DSL Practice: Filter Queries, Pagination and Highlighting
This article details practical usage of Elasticsearch Filter DSL, covering filter query, sort pagination, highlight display and batch operations.
Big Data 173 - Elasticsearch Mapping and Document CRUD Practice
After creating an index, need to set field constraints, called field mapping (mapping).
Elasticsearch Query DSL Practice: match/match_phrase/query_string/multi_match
In-depth explanation of core Query DSL usage in Elasticsearch 7.3, focusing on differences and pitfalls of match, matchphrase, querystring.
Spark Cluster Architecture & Deployment Modes
This is article 71 in the Big Data series, introducing Spark cluster core architecture, deployment mode comparisons, and static/dynamic resource management strategies.
Big Data 171 - Elasticsearch-Head and Kibana 7.3.0 Practice
Introduction to Elasticsearch-Head plugin and Kibana 7.3.0 installation and connectivity points, covering Chrome extension quick access.
Elasticsearch Index Operations & IK Analyzer Practice: 7.3/8.x
This article explains Elasticsearch index CRUD operations and IK analyzer config, covering versions 7.3.0 and 8.15.0.
Big Data 169 - Elasticsearch Getting Started: Index/Document CRUD & Minimum Search Examples
Elasticsearch (ES 7.x/8.x) minimum examples for index creation, document CRUD, query by ID, and _search, with response samples and screenshots to quickly run through the...
Big Data 170 - Elasticsearch 7.3.0 Three-Node Cluster Practice
Elasticsearch 7.3.0 three-node cluster deployment practice tutorial, covering directory creation and permission settings.
Big Data 167 - ELK Elastic Stack Practice: Architecture, Indexing and Troubleshooting
Article introduces core capabilities and common practices of Elasticsearch 8.x, Logstash 8.x, Kibana 8.
Elasticsearch Single Machine Cloud Server Deployment & Operations
Elasticsearch is a distributed full-text search engine, supports single-node mode and cluster mode deployment. Generally, small companies can use Single-Node Mode for the...
Big Data 165 - Apache Kylin Cube7 Practice: Aggregation Group, RowKey and Encoding
Covers Aggregation Group, Mandatory Dimension, Hierarchy Dimension, Joint Dimension usage trade-offs, and explains impact of dictionary encoding, RowKey order.
Apache Kylin 1.6 Streaming Cubing Practice: Kafka to Minute-level OLAP
Kafka→Kylin real-time OLAP pipeline, providing minute-level aggregation queries for common 2025 business scenarios (e-commerce transactions, user behavior...
Spark RDD Deep Dive: Five Key Features
This is article 69 in the Big Data series, deeply analyzing RDD, Spark's core data abstraction, its five key features and design principles.
Spark RDD Creation & Transformation Operations
This is article 70 in the Big Data series, comprehensively explaining Spark RDD's three creation methods and practical usage of common Transformation operators.
Apache Kylin Segment Merge Practice: Manual/Auto Merge, Retention Threshold
Apache Kylin Segment merge practice tutorial, covering manual MERGE Job flow, continuous Segment requirements, Auto Merge multi-level threshold strategy...
Big Data 164 - Apache Kylin Cuboid Pruning Practice: Derived Dimensions & Expansion Control
Cuboid pruning optimization: When there are many dimensions, Cuboid count grows exponentially, causing long build time and storage expansion.
Big Data 161 - Apache Kylin Cube Practice: Modeling, Building and Query Acceleration
Apache Kylin 4.0 Cube modeling and query acceleration method: Complete star modeling with fact tables and dimension tables, design dimensions and measures.
Apache Kylin Incremental Cube & Segment Practice: Daily Partition Column
Using date field of Hive partitioned table as Partition Date Column, split Cube into multiple Segments, incrementally build by range to avoid repeated computation of hist...