MongoDB Translator

The MongoDB translator, known by the type name mongodb, provides a relational view of data that resides in a MongoDB database. This translator is capable of converting Teiid Spring Boot SQL queries into MongoDB based queries. It provides for a full range of SELECT, INSERT, UPDATE and DELETE calls.

MongoDB is a document based "schema-less" database with it own query language. It does not map perfectly with relational concepts or the SQL query language. More and more systems are using NOSQL stores such as MongoDB to improve scalability and performance. For example, applications like storing audit logs, or managing web site data, are well-suited to MongoDB, and do not require the structure of relational databases. MongoDB uses JSON documents as its primary storage unit, and those documents can have additional embedded documents inside the parent document. By using embedded documents, MongoDB co-locates related information to achieve de-normalization that typically requires either duplicate data or joins to achieve querying in a relational database.

For MongoDB to work with Teiid Spring Boot the challenge for the MongoDB translator is to design a MongoDB store that can achieve the balance between relational and document based storage. The advantages of "schema-less" design are great at development time. But "schema-less" design can pose problems during migration between application versions, and when querying data, and making effective use of the returned information.

Since it is hard and may be impossible in certain situations to derive a schema based on existing the MongoDB collection(s), Teiid Spring Boot approaches the problem in reverse compared to other translators. When working with MongoDB, Teiid Spring Boot requires you to define the MongoDB schema upfront, by using Teiid Spring Boot metadata. Because Teiid Spring Boot only allows relational schema as its metadata, you must define your MongoDB schema in relational terms, using tables, procedures, and functions. For the purposes of MongoDB, the Teiid Spring Boot metadata has been extended to provide extension properties that can be defined on a table to convert it into a MongoDB based document. These extension properties let you define how a MongoDB document is structured and stored. Based on the relationships (primary-key, foreign-key) that are defined on a table, and their cardinality (ONE-to-ONE, ONE-to-MANY, MANY-to-ONE), relations between tables are mapped such that related information can be embedded along with the parent document for co-location (as mentioned earlier in this topic). Thus, a relational schema-based design, but document-based storage in MongoDB.

Who is the primary audience for the MongoDB translator?

The above may not satisfy every user’s needs. The document structure in MongoDB can be more complex than what Teiid Spring Boot can currently define. We hope this will eventually catch up in future versions of Teiid Spring Boot. This is currently designed for:

Users who are using relational databases and would like to move/migrate their data to MongoDB to take advantage of scaling and performance without modifying end user applications that they currently run.
Users who are seasoned SQL developers, but do not have experience with MongoDB. This provides a low barrier of entry compared to using MongoDB directly as an application developer.
Users who want to integrate MongoDB-based data with data from other enterprise data sources.

Usage

The name of the translator to use in a virtual database DDL is "mongodb". For example:

CREATE DATABASE nothwind;
USE DATABASE nothwind;
CREATE SERVER local FOREIGN DATA WRAPPER mongodb OPTIONS ("resource-name" 'java:/mongoDS');
CREATE SCHEMA northwind SERVER local;

SET SCHEMA northwind;
IMPORT FROM SERVER local INTO northwind;

The MongoDB translator can derive the metadata based on existing document collections in some scenarios. However, when working with complex documents the interpretation of metadata can be inaccurate. In such cases, you must define the metadata. For example, you can define a schema using DDL, as shown in the following example:

<vdb name="nothwind" version="1">
    <model name="northwind">
        <source name="local" translator-name="mongodb" connection-jndi-name="java:/mongoDS"/>
            <metadata type="DDL"><![CDATA[
                CREATE FOREIGN TABLE  Customer (
                    customer_id integer,
                    FirstName varchar(25),
                    LastName varchar(25)
                ) OPTIONS(UPDATABLE 'TRUE');
            ]]> </metadata>
    </model>
<vdb>

When the following INSERT operation is executed against a table using Teiid Spring Boot, the MongoDB translator creates a document in the MongoDB:

    INSERT INTO Customer(customer_id, FirstName, LastName) VALUES (1, 'John', 'Doe');

{
  _id: ObjectID("509a8fb2f3f4948bd2f983a0"),
  customer_id: 1,
  FirstName: "John",
  LastName: "Doe"
}

If a PRIMARY KEY is defined on the table, then that column name is automatically used as "_id" field in the MongoDB collection, and then the document structure is stored in the MongoDB, as shown in the following examples:

    CREATE FOREIGN TABLE  Customer (
        customer_id integer PRIMARY KEY,
        FirstName varchar(25),
        LastName varchar(25)
    ) OPTIONS(UPDATABLE 'TRUE');

{
  _id: 1,
  FirstName: "John",
  LastName: "Doe"
}

If you defined the composite PRIMARY KEY on Customer table, the document structure that results is shown in the following example:

    CREATE FOREIGN TABLE  Customer (
        customer_id integer,
        FirstName varchar(25),
        LastName varchar(25),
        PRIMARY KEY (FirstName, LastName)
    ) OPTIONS(UPDATABLE 'TRUE');

{
  _id: {
         FirstName: "John",
         LastName:  "Doe"
       },
  customer_id: 1,
}

Data types

The MongoDB translator provides automatic mapping of Teiid Spring Boot data types into MongoDB data types, including BLOBS, CLOBS and XML. The LOB mapping is based on GridFS in MongoDB. Arrays are in the following form:

{
  _id: 1,
  FirstName: "John",
  LastName: "Doe"
  Score: [89, "ninety", 91.0]
}

Users can get individual items in the array using the function array_get, or can transform the array into tabular structure using ARRAYTABLE.

Note	Note that even though embedded documents can also be in arrays, the handling of embedded documents is different from array with scalar values.

Note	The translator does not work with regular Expressions, MongoDB::Code, MongoDB::MinKey, MongoDB::MaxKey, and MongoDB::OID.

Note

In documents that contain values of mixed types for the same key, you must mark the column as unsearchable, or MongoDB will not correctly match predicates against the column. A key is used as a mixed type of it is represented as a string value in one document, and an integer in another. For more information, see the importer.sampleSize property in the following table.

Importer Properties

Importer properties define the behavior of the translator during the metadata import from the physical source.

Importer Properties

Name	Description	Default
excludeTables	Regular expression to exclude the tables from import.	null
includeTables	Regular expression to include the tables from import.	null
sampleSize	Number of documents to sample to determine the structure. If documents have different fields, or fields with different types, this should be greater than 1.	1
fullEmbeddedNames	Whether to prefix embedded table names with their parents, e.g. parent_embedded. If false the name of the table will just be the name of the field - which may lead to conflicts with existing tables or other embedded tables.	false

Name

Description

Default

excludeTables

Regular expression to exclude the tables from import.

null

includeTables

Regular expression to include the tables from import.

null

sampleSize

Number of documents to sample to determine the structure. If documents have different fields, or fields with different types, this should be greater than 1.

fullEmbeddedNames

Whether to prefix embedded table names with their parents, e.g. parent_embedded. If false the name of the table will just be the name of the field - which may lead to conflicts with existing tables or other embedded tables.

false

MongoDB metadata extension properties for building complex documents

Using the preceding DDL, or any other metadata facility, you can map a table in a relational store into a document in MongoDB. However, to make effective use of MongoDB, you must be able to build complex documents that can co-locate related information, so that data can queried in a single MongoDB query. Unlike a relational database, you cannot run join operations in MongoDB. As as a result, unless you can build complex documents, you would have to issue multiple queries to retrieve data and then join it manually. The power of MongoDB comes from its "embedded" documents, its support for complex data types, such as arrays, and its use of an aggregation framework to query them. This translator provides a way to achieve the goals.

When you do not define the complex embedded documents in MongoDB, Teiid Spring Boot can step in for join processing and provide that functionality. However, if you want to make use of the power of MongoDB itself in querying the data and avoid bringing the unnecessary data and improve performance, you need to look into building these complex documents.

MongoDB translator defines two additional metadata properties along with other Teiid metadata properties to aid in building the complex "embedded" documents. For more information about Teiid Spring Boot schema metadata, see r_ddl-metadata-for-schema-objects.adoc. You can use the following metadata properties in your DDL:

teiid_mongo:EMBEDDABLE: Means that data defined in this table is allowed to be included as an "embeddable" document in any parent document. The parent document is referenced by the foreign key relationships. In this scenario, Teiid Spring Boot maintains more than one copy of the data in MongoDB store, one in its own collection, and also a copy in each of the parent tables that have relationship to this table. You can even nest embeddable table inside another embeddable table with some limitations. Use this property on table, where table can exist, encompass all its relations on its own. For example, a "Category" table that defines a "Product"’s category is independent of Product, which can be embeddable in "Products" table.
teiid_mongo:MERGE: Means that data of this table is merged with the defined parent table. There is only a single copy of the data that is embedded in the parent document. Parent document is defined using the foreign key relationships.

Using the above properties and FOREIGN KEY relationships, we will illustrate how to build complex documents in MongoDB.

Note	Usage A given table can contain either the `teiid_mongo:EMBEDDABLE` property or the `teiid_mongo:MERGE` property defining the type of nesting in MongoDB. You cannot use both properties within one table.

ONE-2-ONE Mapping

If your current DDL structure representing ONE-2-ONE relationship is like

    CREATE FOREIGN TABLE  Customer (
        CustomerId integer PRIMARY KEY,
        FirstName varchar(25),
        LastName varchar(25)
    ) OPTIONS(UPDATABLE 'TRUE');

    CREATE FOREIGN TABLE Address (
        CustomerId integer,
        Street varchar(50),
        City varchar(25),
        State varchar(25),
        Zipcode varchar(6),
        FOREIGN KEY (CustomerId) REFERENCES Customer (CustomerId)
     ) OPTIONS(UPDATABLE 'TRUE');

By default, this will produce two different collections in MongoDB, like with sample data it will look like

Customer
{
  _id: 1,
  FirstName: "John",
  LastName: "Doe"
}

Address
{
  _id: ObjectID("..."),
   CustomerId: 1,
   Street: "123 Lane"
   City: "New York",
   State: "NY"
   Zipcode: "12345"
}

You can enhance the storage in MongoDB to a single collection by using teiid_mongo:MERGE extension property on the table’s OPTIONS clause.

    CREATE FOREIGN TABLE  Customer (
        CustomerId integer PRIMARY KEY,
        FirstName varchar(25),
        LastName varchar(25)
    ) OPTIONS(UPDATABLE 'TRUE');

    CREATE FOREIGN TABLE Address (
        CustomerId integer PRIMARY KEY,
        Street varchar(50),
        City varchar(25),
        State varchar(25),
        Zipcode varchar(6),
        FOREIGN KEY (CustomerId) REFERENCES Customer (CustomerId)
     ) OPTIONS(UPDATABLE 'TRUE', "teiid_mongo:MERGE" 'Customer');

this will produce single collection in MongoDB, like

Customer
{
  _id: 1,
  FirstName: "John",
  LastName: "Doe",
  Address:
     {
        Street: "123 Lane",
        City: "New York",
        State: "NY",
        Zipcode: "12345"
     }
}

With the above both tables are merged into a single collection that can be queried together using the JOIN clause in the SQL command. Since the existence of child/additional record has no meaning with out parent table using the "teiid_mongo:MERGE" extension property is right choice in this situation.

Note	The Foreign Key defined on a child table must refer to Primary Keys on both the parent and child tables to form a One-2-One relationship.

ONE-2-MANY Mapping.

Typically there can be more than two (2) tables involved in this relationship. If MANY side is only associated single table, then use teiid_mongo:MERGE property on MANY side of table and define ONE as the parent. If associated with more than single table then use teiid_mongo:EMBEDDABLE.

For example, if you define a virtual database as in the following DDL:

    CREATE FOREIGN TABLE  Customer (
        CustomerId integer PRIMARY KEY,
        FirstName varchar(25),
        LastName varchar(25)
    ) OPTIONS(UPDATABLE 'TRUE');

    CREATE FOREIGN TABLE  Order (
        OrderID integer PRIMARY KEY,
        CustomerId integer,
        OrderDate date,
        Status integer,
        FOREIGN KEY (CustomerId) REFERENCES Customer (CustomerId)
    ) OPTIONS(UPDATABLE 'TRUE');

then a Single Customer can have MANY Orders. There are two options to define the how we store the MongoDB document. If in your schema, the Customer table’s CustomerId is only referenced in Order table (i.e. Customer information used for only Order purposes), you can use

    CREATE FOREIGN TABLE  Customer (
        CustomerId integer PRIMARY KEY,
        FirstName varchar(25),
        LastName varchar(25)
    ) OPTIONS(UPDATABLE 'TRUE');

    CREATE FOREIGN TABLE  Order (
        OrderID integer PRIMARY KEY,
        CustomerId integer,
        OrderDate date,
        Status integer,
        FOREIGN KEY (CustomerId) REFERENCES Customer (CustomerId)
    ) OPTIONS(UPDATABLE 'TRUE', "teiid_mongo:MERGE" 'Customer');

that will produce a single document for Customer table like

{
  _id: 1,
  FirstName: "John",
  LastName: "Doe",
  Order:
  [
     {
       _id: 100,
        OrderDate: ISODate("2000-01-01T06:00:00Z")
        Status: 2
     },
     {
       _id: 101,
        OrderDate: ISODate("2001-03-06T06:00:00Z")
        Status: 5
     }
     ...
   ]
}

If Customer table is referenced in more tables other than Order table, then use "teiid_mongo:EMBEDDABLE" property

    CREATE FOREIGN TABLE Customer (
        CustomerId integer PRIMARY KEY,
        FirstName varchar(25),
        LastName varchar(25)
    ) OPTIONS(UPDATABLE 'TRUE', "teiid_mongo:EMBEDDABLE" 'TRUE');

    CREATE FOREIGN TABLE Order (
        OrderID integer PRIMARY KEY,
        CustomerId integer,
        OrderDate date,
        Status integer,
        FOREIGN KEY (CustomerId) REFERENCES Customer (CustomerId)
    ) OPTIONS(UPDATABLE 'TRUE');

    CREATE FOREIGN TABLE Comments (
        CommentID integer PRIMARY KEY,
        CustomerId integer,
        Comment varchar(140),
        FOREIGN KEY (CustomerId) REFERENCES Customer (CustomerId)
    ) OPTIONS(UPDATABLE 'TRUE');

This creates three different collections in MongoDB.

Customer
{
  _id: 1,
  FirstName: "John",
  LastName: "Doe"
}

Order
{
  _id: 100,
  CustomerId: 1,
  OrderDate: ISODate("2000-01-01T06:00:00Z")
  Status: 2
  Customer:
   {
     FirstName: "John",
     LastName: "Doe"
   }
}

Comment
{
  _id: 12,
  CustomerId: 1,
  Comment: "This works!!!"
  Customer:
   {
     FirstName: "John",
     LastName: "Doe"
   }
}

Here as you can see the Customer table contents are embedded along with other table’s data where they were referenced. This creates duplicated data where multiple of these embedded documents are managed automatically in the MongoDB translator.

Note

All the SELECT, INSERT, DELETE operations that are generated against the tables with "teiid_mongo:EMBEDDABLE" property are atomic, except for UPDATES, as there can be multiple operations involved to update all the copies. Since there are no transactions in MongoDB, Teiid Spring Boot plans to provide automatic compensating transaction framework around this in future releases TEIID-2957.

MANY-2-ONE Mapping.

This is same as ONE-2-MANY, see above to define relationships.

Note	A parent table can have multiple "embedded" and as well as "merge" documents inside it, it not limited so either one or other. However, please note that MongoDB imposes document size is limited can not exceed 16MB.

MANY-2-MANY Mapping.

This can also mapped with combination of "teiid_mongo:MERGE" and "teiid_mongo:EMBEDDABLE" properties (partially). For example if DDL looks like

    CREATE FOREIGN TABLE Order (
        OrderID integer PRIMARY KEY,
        OrderDate date,
        Status integer
    ) OPTIONS(UPDATABLE 'TRUE');

    CREATE FOREIGN TABLE OrderDetail (
        OrderID integer,
        ProductID integer,
        PRIMARY KEY (OrderID,ProductID),
        FOREIGN KEY (OrderID) REFERENCES Order (OrderID),
        FOREIGN KEY (ProductID) REFERENCES Product (ProductID)
    ) OPTIONS(UPDATABLE 'TRUE');

    CREATE FOREIGN TABLE Products (
       ProductID integer PRIMARY KEY,
       ProductName varchar(40)
    ) OPTIONS(UPDATABLE 'TRUE');

you modify the DDL like below, to have

    CREATE FOREIGN TABLE Order (
        OrderID integer PRIMARY KEY,
        OrderDate date,
        Status integer
    ) OPTIONS(UPDATABLE 'TRUE');

    CREATE FOREIGN TABLE OrderDetail (
        OrderID integer,
        ProductID integer,
        PRIMARY KEY (OrderID,ProductID),
        FOREIGN KEY (OrderID) REFERENCES Order (OrderID),
        FOREIGN KEY (ProductID) REFERENCES Product (ProductID)
    ) OPTIONS(UPDATABLE 'TRUE', "teiid_mongo:MERGE" 'Order');

    CREATE FOREIGN TABLE Products (
       ProductID integer PRIMARY KEY,
       ProductName varchar(40)
    ) OPTIONS(UPDATABLE 'TRUE',  "teiid_mongo:EMBEDDABLE" 'TRUE');

That will produce a document like

{
   _id : 10248,
   OrderDate : ISODate("1996-07-04T05:00:00Z"),
   Status : 5
   OrderDetails : [
     {
       _id : {
               OrderID : 10248,
               ProductID : 11
               Products : {
                  ProductID: 11
                  ProductName: "Hammer"
               }
       }
     },
     {
       _id : {
         OrderID : 10248,
         ProductID : 14
         Products : {
             ProductID: 14
             ProductName: "Screw Driver"
         }
       }
     }
   ]
}

Products
{
    {
      ProductID: 11
      ProductName: "Hammer"
    }
    {
      ProductID: 14
      ProductName: "Screw Driver"
    }
}

Limitations

Nested embedding of documents is limited due to capabilities of handling nested arrays is limited in the MongoDB. Nesting of "EMBEDDABLE" property with multiple levels is OK, however more than two levels with MERGE is not recommended. Also, you need to be caution about not exceeding the document size of 16 MB for single row, so deep nesting is not recommended.
JOINS between related tables, MUST use either the "EMBEDDABLE" or "MERGE" properties, otherwise the query will result in error. In order for Teiid Spring Boot to correctly plan and work with JOINS, in the case that any two tables are NOT embedded in each other, use allow-joins=false property on the Foreign Key that represents the relation. For example:

    CREATE FOREIGN TABLE  Customer (
        CustomerId integer PRIMARY KEY,
        FirstName varchar(25),
        LastName varchar(25)
    ) OPTIONS(UPDATABLE 'TRUE');

    CREATE FOREIGN TABLE  Order (
        OrderID integer PRIMARY KEY,
        CustomerId integer,
        OrderDate date,
        Status integer,
        FOREIGN KEY (CustomerId) REFERENCES Customer (CustomerId) OPTIONS (allow-join 'FALSE')
    ) OPTIONS(UPDATABLE 'TRUE');

with the example above, Teiid Spring Boot will create two collections, however when user issues query such as

  SELECT OrderID, LastName FROM Order JOIN Customer ON Order.CustomerId = Customer.CustomerId;

instead of resulting in error, the JOIN processing will happen in the Teiid Spring Boot engine, without the above property it will result in an error.

When you use above properties and carefully design the MongoDB document structure, Teiid Spring Boot translator can intelligently collate data based on their co-location and take advantage of it while querying.

Geo Spatial functions

MongoDB translator enables you to use geo spatial query operators in the "WHERE" clause, when the data is stored in the GeoJSon format in the MongoDB Document. The following functions are available:

CREATE FOREIGN FUNCTION geoIntersects (columnRef string,  type string, coordinates double[][]) RETURNS boolean;
CREATE FOREIGN FUNCTION geoWithin (ccolumnRef string,  type string, coordinates double[][]) RETURNS boolean;
CREATE FOREIGN FUNCTION near (ccolumnRef string,  coordinates double[], maxdistance integer) RETURNS boolean;
CREATE FOREIGN FUNCTION nearSphere (ccolumnRef string, coordinates double[], maxdistance integer) RETURNS boolean;
CREATE FOREIGN FUNCTION geoPolygonIntersects (ref string, north double, east double, west double, south double) RETURNS boolean;
CREATE FOREIGN FUNCTION geoPolygonWithin (ref string, north double, east double, west double, south double) RETURNS boolean;

a sample query looks like

SELECT loc FROM maps where mongo.geoWithin(loc, 'LineString', ((cast(1.0 as double), cast(2.0 as double)), (cast(1.0 as double), cast(2.0 as double))))

Same functions using built-in Geometry type (the versions of the functions in the preceding list will be deprecated and removed in future versions)

CREATE FOREIGN FUNCTION geoIntersects (columnRef string,  geo geometry) RETURNS boolean;
CREATE FOREIGN FUNCTION geoWithin (ccolumnRef string,  geo geometry) RETURNS boolean;
CREATE FOREIGN FUNCTION near (ccolumnRef string, geo geometry, maxdistance integer) RETURNS boolean;
CREATE FOREIGN FUNCTION nearSphere (ccolumnRef string, geo geometry, maxdistance integer) RETURNS boolean;
CREATE FOREIGN FUNCTION geoPolygonIntersects (ref string, geo geometry) RETURNS boolean;
CREATE FOREIGN FUNCTION geoPolygonWithin (ref string, geo geometry) RETURNS boolean;

a sample query looks like

SELECT loc FROM maps where mongo.geoWithin(loc, ST_GeomFromGeoJSON('{"coordinates":[[1,2],[3,4]],"type":"Polygon"}'))

There are various "st_geom.." methods are available in the Geo Spatial function library in Teiid Spring Boot.

Capabilities

MongoDB translator is designed on top of the MongoDB aggregation framework. You must use a MongoDB version that the aggregation framework. Apart from SELECT queries, the MongoDB translator also works with INSERT, UPDATE and DELETE queries.

You can use the MongoDB translator with the following functions:

Grouping.
Matching.
Sorting.
Filtering.
Limits.
Working with LOBs stored in GridFS.
Composite primary and foreign keys.

Native queries

MongoDB source procedures may be created using the teiid_rel:native-query extension. For more information, see Parameterizable native queries in Translators. The procedure will invoke the native-query similar to a direct procedure call with the benefits that the query is predetermined and that result column types are known, rather than requiring the use of ARRAYTABLE or similar functionality.

Direct query procedure

This feature is turned off by default because of the security risk this exposes to execute any command against the source. To enable direct query procedures, set the execution property called SupportsDirectQueryProcedure to true. For more information, see Override the execution properties in as_translators.adoc.

By default the name of the procedure that executes the queries directly is called native. For information about how to change the default name, see Override the execution properties in as_translators.adoc.

The MongoDB translator provides a procedure to execute any ad-hoc aggregate query directly against the source without Teiid Spring Boot parsing or resolving. Since the metadata of this procedure’s results are not known to Teiid Spring Boot, they are returned as an object array containing single blob at array location one(1). This blob contains the JSON document. XMLTABLE can be used construct tabular output for consumption by client applications.

Example MongoDB Direct Query

    select x.* from TABLE(call native('city;{$match:{"city":"FREEDOM"}}')) t,
          xmltable('/city' PASSING JSONTOXML('city', cast(array_get(t.tuple, 1) as BLOB)) COLUMNS city string, state string) x

In the above example, a collection called "city" is looked up with filter that matches the "city" name with "FREEDOM", using "native" procedure and then using the nested tables feature the output is passed to a XMLTABLE construct, where the output from the procedure is sent to a JSONTOXML function to construct a XML then the results of that are exposed in tabular form.

The direct query MUST be in the format

     "collectionName;{$pipeline instr}+"

From Teiid Spring Boot 8.10, MongoDB translator also allows to execute Shell type java script commands like remove, drop, createIndex. For this the command needs to be in format

     "$ShellCmd;collectionName;operationName;{$instr}+"

and example looks like

   "$ShellCmd;MyTable;remove;{ qty: { $gt: 20 }}"

MongoDB translator

MongoDB Translator

results matching ""

No results matching ""