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FulltextSearch
In order to support the natural language search for tons of text contents, we call
String table = "sales";
String column = "feedback";
db_instance.getTable(table).addFulltextSearchable(column);
Then records that contain the column data will be indexed.
Query language is quite similar to the counterpart of Mysql:
String table = "sales";
String query = "feedback against(\" keyword1, keyqord2 + keyword3\")";
ArrayList<Record32KByte> result = db_instance.queryFulltext(table, query);
Where against is the retained keyword of the query grammar. Comma(,), space, and plus(+) stand for the binary logical relationship among keywords respectively as: or, or, and.
For natural languages other than English, user shall implement his own tokenizer that parses the text into entities, words, names etc. Seek how to do it under this package of full-text search.
1 Home
1.1 summary
1.2 System Preparation
1.3 When LunarBase is your best choice
1.4 Benchmark
1.5 Power consumption
2 Data Model And Process
2.1 Why internal big cache
2.2 Memory Management: LunarMMU
2.3 Garbage Collection
2.4 Transaction Log
2.5 JOIN via materialized view
3 Real Time Computation: LunarMax
3.1 In-Memory File System: Memory Estimation
3.2 Configuration
3.3 Use SSD as a cheaper memory
3.4 Data Safety
3.5 HE Server VS. Cluster
3.6 High Availability
4 Create a database
4.1 Three modes
4.2 creation.conf settings
4.3 Table space
4.4 Multiple Instance
4.5 Database Status
4.6 Remove and Restore a table
5 Insertion
5.1 Insert as normal record
5.2 Insert to search engine
6 Query
6.1 Point Query
6.2 Result Handler: register your own event handler
6.3 Interpreter Pattern: complex query conditions
6.4 Range Query
6.5 Full-text Search
6.6 Algebraic Logical Query
8 Deletion
9 Materialized view
9.1 Eventual consistency
9.2 Update
9.3 MVCC in LunarBase
9.4 Easy JOIN via denormalization
9.5 CRUD in view
10 Distributed integration with
10.1 Kafka
10.2 Storm
10.3 Spark
11 Storage: Lunar Virtual File System
13 Roadmap of LunarBase future
15 FAQ