# tMongoDBLookupInput (deprecated) Availability-note[Deprecated](https://help.talend.com/r/en-US/Cloud/labels-on-talend-help-center/availability-deprecated) This content is deprecated. Executes a database query with a strictly defined order which must correspond to the schema definition. Information noteDeprecation: Spark Streaming is deprecated beginning with the R2026-09 release. Use Spark Structured Streaming instead. It passes on the extracted data to tMap in order to provide the lookup data to the main flow. It must be directly connected to a tMap component and requires this tMap to use Reload at each row or Reload at each row (cache) for the lookup flow. ## tMongoDBLookupInput properties for Apache Spark Streaming These properties are used to configure tMongoDBLookupInput running in the Spark Streaming Job framework. The Spark Streaming tMongoDBLookupInput component belongs to the Databases family. The component in this framework is available in Talend Real-Time Big Data Platform and in Talend Data Fabric. ## Basic settings | Properties | Description | | --- | --- | | Property type | Either Built-In or Repository.


Built-In: No property data stored centrally.


Repository: Select the repository file where the
properties are stored. | | MongoDB configuration | Select this check box and in the Component
List drop-down list, select the desired connection component to
reuse the connection details you already defined. | | Schema and Edit
Schema | A schema is a row description. It defines the number of fields
(columns) to be processed and passed on to the next component. When you create a Spark
Job, avoid the reserved word line when naming the
fields.

Click Edit
schema to make changes to the schema. If the current schema is of the Repository type, three options are available:



If a column in the database is a JSON document and you need to read
the entire document, put an asterisk (\*) in the DB
column column, without quotation marks around. | | Collection | Enter the name of the collection to be used.

A MongoDB collection is the equivalent of an RDBMS table and contains
documents. | | Set read preference | Select this check box and from the Read preference
drop-down list that is displayed, select the member to which you need to direct the read
operations.

If you leave this check box clear, the Job uses the default Read preference, that is to
say, uses the primary member in a replica set.

For further information, see MongoDB's documentation about Replication and its Read
preferences. | | Query | Specify the query statement to select documents from the collection specified in the
Collection field.

For
example

```
"{'customer_id':" + row1.customer_id +"}"
```

In this code, *row1* is not the label of the link to
tMongoDBLookupInput, but represents the main row
entering into tMap.

The result of the query must contain only records that match join key you need to use in
tMap. In other words, you must use the schema of the
main flow to tMap to construct the SQL statement here in
order to load only the matched records into the lookup flow.

This approach ensures that no redundant records are loaded into memory and outputted to
the component that follows. | | Mapping | Each column of the schema defined for this component represents a field of the documents
to be read. In this table, you need to specify the parent nodes of these fields, if
any.

For example, in the document reading as
follows

```
{
_id: ObjectId("5099803df3f4948bd2f98391"),
person: { first: "Joe", last: "Walker" }
}
```


The
*first* and the *last*
fields have *person* as their parent node but the *\_id* field does not have any parent node. So once completed, this
Mapping table should read as
follows:

```
Column Parent node path
_id
first "person"
last "person"
``` | | Limit | Enter the maximum number of records to be retrieved. | ## Advanced settings | Properties | Description | | --- | --- | | No query timeout | Select this check box to prevent MongoDB servers from stopping idle
cursors at the end of 10-minute inactivity of these cursors. In this
situation, an idle cursor will stay open until either the results of
this cursor are exhausted or you manually close it using the
cursor.close() method.

A cursor for MongoDB is a pointer to the result set of a query. By
default, that is to say, with this check box being clear, a MongoDB
server automatically stops idle cursors after a given inactivity period
to avoid excess memory use. For further information about MongoDB
cursors, see https://docs.mongodb.org/manual/core/cursors/. | ## Usage | Usage guidance | Description | | --- | --- | | **Usage rule** | This component is used as a start component and requires an output link.

This component should use a tMongoDBConfiguration component present in the same Job to connect
to a MongoDB database. You need to drop a tMongoDBConfiguration component alongside this component and
configure the Basic settings of this component
to use tMongoDBConfiguration.

This component, along with the Spark Streaming component Palette it belongs to, appears
only when you are creating a Spark Streaming Job.

Note that in this documentation, unless otherwise explicitly stated, a scenario presents
only Standard Jobs, that is to say traditional
Talend
data
integration Jobs. | | Spark Connection | In the Spark
Configuration tab in the Run
view, define the connection to a given Spark cluster for the whole Job. In
addition, since the Job expects its dependent jar files for execution, you must
specify the directory in the file system to which these jar files are
transferred so that Spark can access these files:



This connection is effective on a per-Job basis. | **Related concepts** * [Reading and writing data in MongoDB using a Spark Streaming Job](https://help.qlik.com/talend/en-US/components/8.0/mongodb/tmongodblookupinput-tmongodbconfiguration-ts3configuration-reading-and-writing-data-in-mongodb-using-spark-streaming-job-spark-stream-component-in-this)