Learn about developing hybrid apps using IBM Informix

1. © 2015 IBM Corporation
DMX-2904 : Developing Hybrid
Applications With Informix: Your Data
Model Should Not Restrict Data
Access
Erika Von Bargen (vonbarg@us.ibm.com),
Shawn Moe (smoe@us.ibm.com)
Thursday October 29, 2015
08:30 AM-09:30 AM

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Performance is based on measurements and projections using standard IBM benchmarks in a
controlled environment. The actual throughput or performance that any user will experience will vary
depending upon many factors, including considerations such as the amount of multiprogramming in the
user’s job stream, the I/O configuration, the storage configuration, and the workload processed.
Therefore, no assurance can be given that an individual user will achieve results similar to those stated
here.
Please Note:
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3. Agenda
• The Informix Wire Listener
• Unified Data Access
• MongoDB API
• REST API
• Hybrid Operations
• SQL passthrough
• Joins
• Application examples
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4. The Informix Wire Listener
• The wire listener is a mid-tier gateway server that enables
communication between MongoDB and REST applications and
the Informix database server.
• It’s a software layer that translates MongoDB protocol and REST
commands into Informix SQL for storage and processing of data
• It’s a Java application packaged as an executed JAR file –
jsonListener.jar – that communicates to the Informix server using
the Informix JDBC driver.
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5. NoSQL & Listener Architecture
4
REST
Wire Listener
Protocol conversion
Mongo
DB wire
protocol
REST
Informix
Relational, JSON,
Timeseries Storage
JDBC,
SQL

6. The Informix Wire Listener: Unified Data Access
• The Informix wire listener unified access to the following types of data:
JSON data, stored in “collections”
Relational data
Time Series data
Spatial data
• The flexibility of JSON enables us to represent all of the above as a
JSON document collection.
• When you run an operation, the listener performs a lookup of the type
of table you are querying to determine if it's a collection, relational, or
time series table
• A query processor will build the equivalent SQL statement for the table
type you are querying
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7. Unified Data Access
• JSON Data / Collections
JSON documents are transformed into a BSON representation and are
stored in a BSON column of a relational table.
Queries run against collections are rewritten by the listener to SQL
queries using BSON manipulation functions
Indexes can be created on fields of the JSON/BSON document using
Informix functional indexes.
Client access based on MongoDB API functions
• Same capabilities available in MongoDB API are also available through the
REST API
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8. • Relational Data:
The columns of a relational table are mapped to the fields of a
JSON document.
MongoDB API calls can be run on relational tables as though the
tables were document collections.
• For example, the same call to create an index on a field of a document
would create an index on a column of the same name.
All basic operations available with document collections (insert,
update, delete, query, aggregations) can be used without
modification against a relational table.
• Story: We had a user, who was using a collection, create a relational
table that had the same name as the collection and had columns with
corresponding data types and names as the fields in the document.
The application worked without modification.
Informix row types are represented as sub-documents.
Unified Data Access

9. • Time Series Data:
Informix time series data is stored in a way that is similar to a
column-store database.
The present strategy is to use the Informix Virtual Table Interface
(VTI) to make the TimeSeries data appear to be a relational table.
This virtual table can then be accessed by the Mongo & REST
APIs.
• Spatial Data:
Spatial data can be inserted into a document collection using the
GeoJSON specification.
Informix functional indexes enable users to efficiently query spatial
data.
Unified Data Access: Time Series & Spatial
Data

10. The Mongo Wire Listener
• The Mongo listener (listener.type=mongo) communicates with clients
using the MongoDB wire protocol
Allows MongoDB clients to communicate with Informix via the
listener
Mongo collections are mapped to special collection tables in
Informix that contain a BSON column
• Supports hybrid access
Not only can Mongo client applications access BSON (collection)
data, but Informix relational and timeseries data as well
Same Mongo API functions (find, insert, update, delete,
findAndModify, aggregate, count, explain, etc) can be used on all
Informix data types
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11. MongoDB Application Driver Compatibility
• Use any of the MongoDB client drivers and frameworks against the
Informix database server
Little to no change required when running MongoDB programs
Informix listens on the same default port as mongo, no need to change.
• Leverage the different MongoDB drivers available
• Other MongoDB Community Drivers are also available
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C Perl
C# PHP
Java Python
JavaScript Ruby
Node.js Scala

12. Mongo Operations
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Action Mongo Syntax
Insert db.customer.insert( { name: “John", age: 21 } )
Query (select all) db.customer.find()
Query with condition db.customer.find( {age: { $gt:21 } } )
Update db.customer.update(
{ age: { $gt: 18} }, { $set: { status: “Adult" } },
{ multi: true }
)
Delete db.customer.remove( { age: { $gt:21 } } )
Create Index db.customer.ensureIndex(
{ name : 1, age : -1 }
)
Use the exact same syntax no matter if the underlying Informix
data storage is JSON, relational, or time series.

13. The REST wire listener
• The REST listener (listener.type=rest) communicates with clients
using REST
Allows driverless access to Informix via the listener
• Eliminating middle tier of three-tier architecture in favor of a two-tier
client database model simplifies development, debugging,
deployment and speed time to market.
• Eliminates reliance on vendor-supplied proprietary drivers
• Supports hybrid access
REST access to JSON, relational, and timeseries data
Same REST methods (GET, POST, PUT, DELETE) work the
same way no matter the underlying data type
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14. RESTful Data Access
• URL Structure
http://<host>[:port]/<db>/<collection>
where <collection> is the name of a JSON collection, relational table, or
timeseries table/VTI
• REST HTTP methods:
GET = query a resource
POST = create a resource (insert)
PUT = update a resource
DELETE = delete a resource
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15. REST: HTTP method overview
14
Path
Descriptio
n
Text Text Text

16. REST Examples
• Query: GET /test/people
Get all documents from the namespace test.people (db=test,
collection=people)
Example result
[{"_id":{"$oid":"533501be27784337861702c5"},"name":"lance"},
{"_id":{"$oid":"533501c227784337861702c6"},"name":"brian"},
{"_id":{"$oid":"533501c627784337861702c7"},"name":"erika"}]
The result is a JSON array of documents.
• Query with condition:
GET /test/users?query={age:{$gt:30}}&sort={age:1}
&fields:{firstName:1, age:1, _id:0}
Get all documents from the namespace test.users (db=test,
collection=users) whose age > 30, sort the results by age and filter
the fields in the response

17. REST Examples
• Insert:
POST to collection namespace, providing your JSON document to insert in
the data of the HTTP request
POST /test/users
Data:
{firstName:"John",lastName:"Doe",age:31}
Response:
{"n":1, "ok":true}
• Delete:
Send a DELETE request to a collection namespace, providing your
query condition in the URL
DELETE /test/users?query={name:“Larry”}
Response:
{"n":1, "ok":true}

18. REST Examples
• Update:
Send a PUT to a collection namespace, providing your query condition in
the URL and the update operation in the data of the HTTP request
PUT /test/users?query={firstName:“Larry”}
Data:
{"$set": {age : 25}}
Response:
{"n":1, "ok":true}

19. Hybrid Operations: SQL Passthrough
• Allows users of Mongo and REST clients to execute pure SQL
statements
• Mixes the ease of use of JSON documents with the power of SQL
processing
• Special permission is needed to execute raw SQL statements
• Listener properties file must have it enabled:
security.sql.passthrough=true
• If authentication is used, you must have the role sql or sqlAnyDatabase
• Uses a pseudo collection “system.sql” to authenticate SQL queries
and a new $sql query operator to instruct the listener to execute the
JSON value that follows as a raw SQL statement
• Results are packaged into JSON documents so clients can work with
the results as they would a collection.
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20. Hybrid Operations: SQL Passthrough
• Example
INSERT, UPDATE, and DELETE SQL will return a document containing
the number of rows effected.
db.getCollection("system.sql").findOne({ "$sql": "delete from cust_calls where
(call_dtime + interval(5) year to year) < current" })
Result: { "n" : 7 }
• Example
QUERY
db.getCollection("system.sql").find({ "$sql": "select
c.customer_num,o.customer_num as order_cust,count(order_num) as
order_count from customer c left outer join orders o on c.customer_num
= o.customer_num group by 1, 2 order by 2" })
Result:
{ "customer_num" : 113, "order_cust" : null, "order_count" : 0 }
{ "customer_num" : 114, "order_cust" : null, "order_count" : 0 }
{ "customer_num" : 101, "order_cust" : 101, "order_count" : 1 }
{ "customer_num" : 104, "order_cust" : 104, "order_count" : 4 }
{ "customer_num" : 106, "order_cust" : 106, "order_count" : 2 }
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21. Hybrid Operations: Joins
• Hybrid applications may need to join and combine data from
different data sources
• The Informix wire listener enables the ability to run JOIN
queries
Collection-to-collection joins
Relational-to-relational joins
Collection-to-relational joins
• Join support is available to both REST and MongoDB clients
via an extension of the Mongo API
• Join queries are done by querying the pseudo system.join
collection and providing a query document that represents the
join specification
The listener automatically determines the types of objects being
joined and generates the correct SQL syntax to join disparate
data
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22. Hybrid Operations: Joins
• Syntax
> db.getCollection(“system.join”).find(
{ $collections :
{
“tabName1” : { $project: {…}, $where: {…} },
“tabName2” : {$project: {…}, $where: {…} },
…
},
“$condition” : { join_condition_specification }
}
)
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23. Hybrid Operations: Joins
• Example
Get the customers orders that totaled more than $100. Join the
customers and orders collections/tables on the customer_num
field/column where the order total is greater than 100.
> db.getCollection(“system.join”).find(
{ “$collections” :
{ “customers” :
{ “$project”: { customer_num: 1, name: 1, phone: 1 } },
“orders” :
{ “$project”: { order_num: 1, nitems: 1, total: 1, _id: 0 },
“$where” : { total : { “$gt”: 100 } } }
},
“$condition” : { “customers.customer_num” : “orders.customer_num” }
}
)
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Same query syntax regardless of where “customers” and
“orders” are JSON collections, relational tables, or both.

24. Sample Applications
• Informix sample applications are available for Java, JavaScript
(Node.js), Python, and Ruby at
https://github.com/ibm-informix/informix-client-examples
Each programming language has both REST and Mongo sample
applications
• “HelloWorld” samples show basic database operations such as
inserting, querying, updating.
• “HelloGalaxy” samples go into more in depth topics such as
transactions, commands, joins, and hybrid operations.
• Samples applications can be run in a local environment or
deployed to the Informix TimeSeries DB service in Bluemix
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25. Python Example Application: Mongo
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26. Python Example Application: REST
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27. Conclusion
• Informix and the wire listener offer
Support for access to hybrid data in a single storage engine:
• schema-less JSON document collections, structured relational data,
and high performing timeseries data
A unified data manipulation language:
• A NoSQL query syntax that works on all underlying data storage
types
A RESTful API for driverless data access
A MongoDB API that enables access from a large community of
MongoDB language drivers
• All of this enables Informix to provide a hybrid database
solution that is uniquely capable of
simplifying application development,
reducing the time to market,
and increasing the opportunity to create compelling applications.
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