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# oracle-json sample NodeJS scripts presenting different features of MongoDB API and Oracle JSON Database
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### 02_basic_demo.js
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This script contains examples describin Oracle API for MongoDB support for basic native MongoDB statements, like insert, insertMany, update, and find
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### 03_expr.js
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This script contains an example of using $sql operator allowing for executing SQL statements against an Oracle API for MongoDB instance and how it can be used as a replacement for $expr native MongoDB operator
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### 04_mongo_views.js
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This script contains an example proving that MongoDB views are fully supported by Oracle API for MongoDB, including their creation using native MongoDB commands
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### 05_oracle_views.js
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This script contains examples of using Oracle JSON Collection Views and JSON Duality Views in queries expressed by using native MongoDB commands.
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examples cover creation, data loading (JSON Duality Views), querying as well as execution plans generation.
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### 06_partial_indexes.js
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This script contains example comparing native MongoDB partial indexes (not supported in exactly the same form by Oracle API for MongoDB) and Oracle function-based indexes, which can be used as a partial indexes replacements, but also offer full functionality of building indexing expressions, which are not limited to indexing only a part of the data.
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### 07_ps_indexes.js
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This script contains examples of using Oracle-specific Path-Subsetting indexes to increase the performance of MongoDB native commands. Examples cover creation such indexes by executing native MongoDB commands ($sql operator) as well as querying data and generating execution plans, which use such indexes
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### 08_mv_indexes.js
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This is the second script presenting another type of Oracle-specific indexes - Multivalue Indexes with examples of their creation and usage in MongoDB native queries, including displaying execution plans
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### 09_transactions.js
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This script presents full ACID transactions support provided by Oracle Database and Oracle API for MongoDB to MongoDB native applications: no limitations for size and time and availability even in case of a single-node/non-cluster/non-sharding architecture

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