Amazon SQS Consumer

Use the Amazon SQS Consumer origin to read data from queues in Amazon Simple Queue Services (SQS). The origin can use multiple threads to enable parallel processing of data. To read data from Amazon S3, use the Amazon S3 origin. For information about supported versions, see Supported Systems and Versions.

When you configure the Amazon SQS Consumer origin, you define the region and the set of queue name prefixes to use. These properties determine the objects that the origin processes. You configure the authentication method that the origin uses to connect to Amazon Simple Queue Services.

You can optionally include Amazon SQS message attributes and sender attributes in records as record header attributes.

You can also use a connection to configure the origin.

Authentication Method

You can configure the Amazon SQS Consumer origin to authenticate with Amazon Web Services (AWS) using an instance profile or AWS access keys. When accessing a public bucket, you can connect anonymously using no authentication.

For more information about the authentication methods and details on how to configure each method, see Security in Amazon Stages.

Queue Name Prefix

The Amazon SQS Consumer origin uses the queue name prefix to determine the queues to process. You can define multiple queue name prefixes.

When you specify the queue name prefix, enter a string that represents the beginning of the queue names that you want to use. The origin processes data from every queue with a matching prefix. You cannot use wildcards within the queue name prefix.

For example, say you have the following queues:

sales-eu-france
sales-eu-germany
sales-us
sales-egypt

If you use "sales" as the prefix, the origin processes messages from all of the queues.

If you use "sales-eu" as the prefix, the origin processes only sales-eu-france and sales-eu-germany.

If you use "sales-e" as the prefix, the origin processes all queues except for sales-us.

Multithreaded Processing

The Amazon SQS Consumer origin performs parallel processing and enables the creation of a multithreaded pipeline. The Amazon SQS Consumer origin uses multiple concurrent threads based on the Max Threads property.

When performing multithreaded processing, the Amazon SQS Consumer origin determines the number of queues to process and creates the specified number of threads. When there are more queues than threads, the queues are divided up and assigned to different threads. Each thread processes data from a specific set of queues and cycles round-robin through the set of queues.

When a thread requests data from a queue, the queue returns messages based on the configured Number of Messages per Request property. The thread creates a batch of data and passes the batch to an available pipeline runner. After processing the batch, the thread continues to the next assigned queue.

A pipeline runner is a sourceless pipeline instance - an instance of the pipeline that includes all of the processors, executors, and destinations in the pipeline and handles all pipeline processing after the origin. Each pipeline runner processes one batch at a time, just like a pipeline that runs on a single thread. When the flow of data slows, the pipeline runners wait idly until they are needed, generating an empty batch at regular intervals. You can configure the Runner Idle Time pipeline property to specify the interval or to opt out of empty batch generation.

Multithreaded pipelines preserve the order of records within each batch, just like a single-threaded pipeline. But the order that batches are written to destinations is not ensured.

For example, say you set the Max Threads property to 5 and the origin is configured to process 20 queues. When you start the pipeline, the origin creates five threads, and Data Collector creates a matching number of pipeline runners. Each thread is assigned 4 queues to process. Each thread cycles through the queues, creating one batch of data at a time and passing it to a pipeline runner for processing.

At any given moment, the five pipeline runners can each process a batch, so this multithreaded pipeline processes up to five batches at a time. When incoming data slows, the pipeline runners sit idle, available for use as soon as the data flow increases.

For more information about multithreaded pipelines, see Multithreaded Pipeline Overview.

Including SQS Message Attributes

The Amazon SQS Consumer origin can include SQS message attributes in records as record header attributes. You can add different groups of SQS attributes to records based on the SQS Message Attribute Level that you select:

Basic - Includes some basic SQS attributes.
All Attributes - Includes all standard SQS attributes.

SQS attributes are added to record header attributes using the following naming convention: sqs.<SQS attribute name>.

The following table lists the SQS attributes included in each attribute level:


SQS Attribute Level	Description
Basic	Includes the following standard SQS attributes: sqs.messageId - The SQS message ID. sqs.queueNamePrefix - The queue name prefix that you configured for the stage. sqs.region - The AWS region for the message.
All Attributes	Includes the standard SQS attributes listed above and the following additional SQS attributes: sqs.body - The full raw message body. sqs.bodyMd5 - The MD5 hash of the raw message body. sqs.queueUrl - The full URL for the originating queue. sqs.attrsMd5 - The MD5 hash of the all SQS attributes included in the message.

For more information about SQS message attributes, see the Amazon SQS documentation.

Including Sender Attributes

In addition to SQS message attributes, you can include sender attributes in record headers. Sender attributes are custom attributes included in messages by the message sender.

To include message sender attributes, you perform the following steps:

Set the SQS Message Attribute Level property to All Attributes.
Configure the SQS Sender Attribute property, adding the name of each attribute that you want to include in the record.

SQS attributes are added to record header attributes using the following naming convention: sqs.messageAttr.<sender attribute name>.

For example, a senderId attribute appears in the record header as sqs.messageAttr.senderId.

Data Formats

The Amazon SQS Consumer origin processes data differently based on the data format. The Amazon SQS Consumer can process the following types of data:

Avro

Generates a record for every message. Includes a precision and scale field attribute for each Decimal field.

The origin includes the Avro schema in an avroSchema record header attribute. You can use one of the following methods to specify the location of the Avro schema definition:

Message/Data Includes Schema - Use the schema in the message.
In Pipeline Configuration - Use the schema that you provide in the stage configuration.
Confluent Schema Registry - Retrieve the schema from Confluent Schema Registry. Confluent Schema Registry is a distributed storage layer for Avro schemas. You can configure the origin to look up the schema in Confluent Schema Registry by the schema ID embedded in the message or by the schema ID or subject specified in the stage configuration.
You must specify the method that the origin uses to deserialize the message. If the Avro schema ID is embedded in each message, set the key and value deserializers to Confluent on the Kafka tab.

Using a schema in the stage configuration or retrieving a schema from Confluent Schema Registry overrides any schema that might be included in the message and can improve performance.

Binary

Generates a record with a single byte array field at the root of the record.

When the data exceeds the user-defined maximum data size, the origin cannot process the data. Because the record is not created, the origin cannot pass the record to the pipeline to be written as an error record. Instead, the origin generates a stage error.

Delimited

Generates a record for each delimited line.

The CSV parser that you choose determines the delimiter properties that you configure and how the stage handles parsing errors. You can specify if the data includes a header line and whether to use it. You can define the number of lines to skip before reading, the character set of the data, and the root field type to use for the generated record.

You can also configure the stage to replace a string constant with null values and to ignore control characters.

For more information about reading delimited data, see Reading Delimited Data.

JSON

Generates a record for each JSON object. You can process JSON files that include multiple JSON objects or a single JSON array.

When an object exceeds the maximum object length defined for the origin, the origin processes the object based on the error handling configured for the stage.

Log

Generates a record for every log line.

When a line exceeds the user-defined maximum line length, the origin truncates longer lines.

You can include the processed log line as a field in the record. If the log line is truncated, and you request the log line in the record, the origin includes the truncated line.

You can define the log format or type to be read.

Protobuf

Generates a record for every protobuf message. By default, the origin assumes messages contain multiple protobuf messages.

Protobuf messages must match the specified message type and be described in the descriptor file.

When the data for a record exceeds 1 MB, the origin cannot continue processing data in the message. The origin handles the message based on the stage error handling property and continues reading the next message.

For information about generating the descriptor file, see Protobuf Data Format Prerequisites.

SDC Record

Generates a record for every record. Use to process records generated by a Data Collector pipeline using the SDC Record data format.

For error records, the origin provides the original record as read from the origin in the original pipeline, as well as error information that you can use to correct the record.

When processing error records, the origin expects the error file names and contents as generated by the original pipeline.

Text

Generates a record for each line of text or for each section of text based on a custom delimiter.

When a line or section exceeds the maximum line length defined for the origin, the origin truncates it. The origin adds a boolean field named Truncated to indicate if the line was truncated.

For more information about processing text with a custom delimiter, see Text Data Format with Custom Delimiters.

XML

Generates records based on a user-defined delimiter element. Use an XML element directly under the root element or define a simplified XPath expression. If you do not define a delimiter element, the origin treats the XML file as a single record.

Generated records include XML attributes and namespace declarations as fields in the record by default. You can configure the stage to include them in the record as field attributes.

You can include XPath information for each parsed XML element and XML attribute in field attributes. This also places each namespace in an xmlns record header attribute.

When a record exceeds the user-defined maximum record length, the origin skips the record and continues processing with the next record. It sends the skipped record to the pipeline for error handling.

Use the XML data format to process valid XML documents. For more information about XML processing, see Reading and Processing XML Data.

Tip: If you want to process invalid XML documents, you can try using the text data format with custom delimiters. For more information, see Processing XML Data with Custom Delimiters.

Configuring an Amazon SQS Consumer

Configure an Amazon SQS Consumer origin to read messages from Amazon SQS.

In the Properties panel, on the General tab, configure the following properties:


General Property	Description
Name	Stage name.
Description	Optional description.
On Record Error	Error record handling for the stage: Discard - Discards the record. Send to Error - Sends the record to the pipeline for error handling. Stop Pipeline - Stops the pipeline.

On the SQS tab, configure the following properties:


SQS Property	Description
Connection	Connection that defines the information required to connect to an external system. To connect to an external system, you can select a connection that contains the details, or you can directly enter the details in the pipeline. When you select a connection, Control Hub hides other properties so that you cannot directly enter connection details in the pipeline. To create a new connection, click the Add New Connection icon: . To view and edit the details of the selected connection, click the Edit Connection icon: .
Authentication Method	Authentication method used to connect to Amazon Web Services (AWS): AWS Keys - Authenticates using an AWS access key pair. Instance Profile - Authenticates using an instance profile associated with the Data Collector EC2 instance. None - Connects to a public bucket using no authentication.
Access Key ID	AWS access key ID. Required when using AWS keys to authenticate with AWS.
Secret Access Key	AWS secret access key. Required when using AWS keys to authenticate with AWS. Tip: To secure sensitive information such as access key pairs, you can use runtime resources or credential stores.
Assume Role	Temporarily assumes another role to authenticate with AWS.
Role ARN	Amazon resource name (ARN) of the role to assume, entered in the following format: `arn:aws:iam::<account_id>:role/<role_name>` Where `<account_id>` is the ID of your AWS account and `<role_name>` is the name of the role to assume. You must create and attach an IAM trust policy to this role that allows the role to be assumed. Available when assuming another role.
Role Session Name	Optional name for the session created by assuming a role. Overrides the default unique identifier for the session. Available when assuming another role.
Session Timeout	Maximum number of seconds for each session created by assuming a role. The session is refreshed if the pipeline continues to run for longer than this amount of time. Set to a value between 3,600 seconds and 43,200 seconds. Available when assuming another role.
Set Session Tags	Sets a session tag to record the name of the currently logged in StreamSets user that starts the pipeline or the job for the pipeline. AWS IAM verifies that the user account set in the session tag can assume the specified role. Select only when the IAM trust policy attached to the role to be assumed uses session tags and restricts the session tag values to specific user accounts. When cleared, the connection does not set a session tag. Available when assuming another role.
Region	AWS region to connect to. Select one of the available regions. To specify an endpoint to connect to, select Other.
Endpoint	Endpoint to connect to when you select Other for the region. Enter the endpoint name.
Queue Name Prefix	The common prefix for the queues to process. Wildcards are not allowed.
External ID	External ID included in an IAM trust policy that allows the specified role to be assumed. Available when assuming another role.
Number of Messages per Request	The number of messages to request for each request. The maximum allowed by Amazon Simple Queue Service is 10 messages. Default is 10.
Max Batch Size (records)	Maximum number of records processed at one time. Honors values up to the Data Collector maximum batch size. Default is 1000. The Data Collector default is 1000.
Max Batch Wait Time (ms)	Number of milliseconds to wait before sending a partial or empty batch.
Max Threads	The number of threads to use to process messages. Default is `${runtime:availableProcessors()}`, which returns the number of Data Collector processors that are available when the pipeline starts.
Poll Wait Time (Seconds)	Number of seconds to wait for a request response. Specify a wait time to use Amazon SQS long polling to minimize the effects of empty responses. When configured, the origin waits the specified number of seconds for messages before continuing to another queue. Use -1 to opt out of this property. When opting out, when a queue has no data, the origin continues immediately to the next queue.
SQS Message Attribute Level	Determines the message attributes that are included in the record as record header attributes. Select one of the following options: No Attributes - The origin includes no attributes included in the message in the record. Basic Attributes - The origin includes a small set of basic SQS attributes in the record. All Attributes - The origin includes all SQS-generated attribute information, such as the message body and queue URL. When specified, can also include SQS attributes generated by the message sender. For more information about the attributes included in the message, see Including SQS Message Attributes.
Include Sender SQS Attributes	When including all SQS message attributes in the record header attribute, you can also include attributes generated by the sender of the messages. Specify the message sender attributes that you want to include. Enter the exact attribute name.

On the Advanced tab, optionally configure proxy information:


Advanced Property	Description
Connection Timeout	Seconds to wait for a response before closing the connection.
Socket Timeout	Seconds to wait for a response to a query.
Retry Count	Maximum number of times to retry requests.
Use Proxy	Specifies whether to use a proxy to connect.
Proxy Host	Proxy host.
Proxy Port	Proxy port.
Proxy User	User name for proxy credentials.
Proxy Password	Password for proxy credentials. Tip: To secure sensitive information such as user names and passwords, you can use runtime resources or credential stores.
Proxy Domain	Optional domain name for the proxy server.
Proxy Workstation	Optional workstation for the proxy server.

On the Data Format tab, configure the following property:


Data Format Property	Description
Data Format	Type of data to be read. Use one of the following options: Avro Binary Delimited JSON Log Text Protobuf SDC Record XML

For Avro data, on the Data Format tab, configure the following properties:


Avro Property	Description
Avro Schema Location	Location of the Avro schema definition to use when processing data: Message/Data Includes Schema - Use the schema in the message. In Pipeline Configuration - Use the schema provided in the stage configuration. Confluent Schema Registry - Retrieve the schema from Confluent Schema Registry. Using a schema in the stage configuration or in Confluent Schema Registry can improve performance.
Avro Schema	Avro schema definition used to process the data. Overrides any existing schema definitions associated with the data. You can optionally use the `runtime:loadResource` function to load a schema definition stored in a runtime resource file.
Schema Registry URLs	Confluent Schema Registry URLs used to look up the schema. To add a URL, click Add and then enter the URL in the following format: `http://<host name>:<port number>`
Basic Auth User Info	User information needed to connect to Confluent Schema Registry when using basic authentication. Enter the key and secret from the `schema.registry.basic.auth.user.info` setting in Schema Registry using the following format: `<key>:<secret>` Tip: To secure sensitive information such as user names and passwords, you can use runtime resources or credential stores.
Lookup Schema By	Method used to look up the schema in Confluent Schema Registry: Subject - Look up the specified Avro schema subject. Schema ID - Look up the specified Avro schema ID. Embedded Schema ID - Look up the Avro schema ID embedded in each message. Overrides any existing schema definitions associated with the message.
Schema Subject	Avro schema subject to look up in Confluent Schema Registry. If the specified subject has multiple schema versions, the stage uses the latest schema version for that subject. To use an older version, find the corresponding schema ID, and then set the Look Up Schema By property to Schema ID.
Schema ID	Avro schema ID to look up in Confluent Schema Registry.

For binary data, on the Data Format tab and configure the following property:


Binary Property	Description
Max Data Size (bytes)	Maximum number of bytes in the message. Larger messages cannot be processed or written to error.

For delimited data, on the Data Format tab, configure the following properties:


Delimited Property	Description
Delimiter Format Type	Delimiter format type. Use one of the following options: Default CSV - File that includes comma-separated values. Ignores empty lines in the file. RFC4180 CSV - Comma-separated file that strictly follows RFC4180 guidelines. MS Excel CSV - Microsoft Excel comma-separated file. MySQL CSV - MySQL comma-separated file. Tab-Separated Values - File that includes tab-separated values. PostgreSQL CSV - PostgreSQL comma-separated file. PostgreSQL Text - PostgreSQL text file. Custom - File that uses user-defined delimiter, escape, and quote characters. Multi Character Delimited - File that uses multiple user-defined characters to delimit fields and lines, and single user-defined escape and quote characters. Available when using the Apache Commons parser type.
Header Line	Indicates whether a file contains a header line, and whether to use the header line.
Allow Extra Columns	Allows processing records with more columns than exist in the header line. Available when using the Apache Commons parser to process data with a header line.
Extra Column Prefix	Prefix to use for any additional columns. Extra columns are named using the prefix and sequential increasing integers as follows: `<prefix><integer>`. For example, `_extra_1`. Default is `_extra_`. Available when using the Apache Commons parser to process data with a header line while allowing extra columns.
Max Record Length (chars)	Maximum length of a record in characters. Longer records are not read. This property can be limited by the Data Collector parser buffer size. For more information, see Maximum Record Size. Available when using the Apache Commons parser.
Delimiter Character	Delimiter character. Select one of the available options or use Other to enter a custom character. You can enter a Unicode control character using the format `\uNNNN`, where N is a hexadecimal digit from the numbers 0-9 or the letters A-F. For example, enter `\u0000` to use the null character as the delimiter or `\u2028` to use a line separator as the delimiter. Default is the pipe character ( \| ). Available when using the Apache Commons parser with a custom delimiter format.
Multi Character Field Delimiter	Characters that delimit fields. Default is two pipe characters (\|\|). Available when using the Apache Commons parser with the multi-character delimiter format.
Multi Character Field Delimiter	Characters that delimit fields. Default is two pipe characters (\|\|). Available when using the Apache Commons parser with the multi-character delimiter format.
Escape Character	Escape character. Available when using the Apache Commons parser with the custom or multi-character delimiter format. Also available when using the Univocity parser.
Quote Character	Quote character. Available when using the Apache Commons parser with the custom or multi-character delimiter format. Also available when using the Univocity parser.
Enable Comments	Allows commented data to be ignored for custom delimiter format. Available when using the Apache Commons parser.
Comment Marker	Character that marks a comment when comments are enabled for custom delimiter format. Available when using the Apache Commons parser.
Lines to Skip	Number of lines to skip before reading data.
Compression Format	The compression format of the files: None - Processes only uncompressed files. Compressed File - Processes files compressed by the supported compression formats. Archive - Processes files archived by the supported archive formats. Compressed Archive - Processes files archived and compressed by the supported archive and compression formats.
File Name Pattern within Compressed Directory	For archive and compressed archive files, file name pattern that represents the files to process within the compressed directory. You can use UNIX-style wildcards, such as an asterisk or question mark. For example, .json. Default is , which processes all files.
CSV Parser	Parser to use to process delimited data: Apache Commons - Provides robust parsing and a wide range of delimited format types. Univocity - Can provide faster processing for wide delimited files, such as those with over 200 columns. Default is Apache Commons.
Max Columns	Maximum number of columns to process per record. Available when using the Univocity parser.
Max Character per Column	Maximum number of characters to process in each column. Available when using the Univocity parser.
Skip Empty Lines	Allows skipping empty lines. Available when using the Univocity parser.
Allow Extra Columns	Allows processing records with more columns than exist in the header line. Available when using the Apache Commons parser to process data with a header line.
Extra Column Prefix	Prefix to use for any additional columns. Extra columns are named using the prefix and sequential increasing integers as follows: `<prefix><integer>`. For example, `_extra_1`. Default is `_extra_`. Available when using the Apache Commons parser to process data with a header line while allowing extra columns.
Max Record Length (chars)	Maximum length of a record in characters. Longer records are not read. This property can be limited by the Data Collector parser buffer size. For more information, see Maximum Record Size. Available when using the Apache Commons parser.
Ignore Empty Lines	Allows empty lines to be ignored. Available when using the Apache Commons parser with the custom delimiter format.
Root Field Type	Root field type to use: List-Map - Generates an indexed list of data. Enables you to use standard functions to process data. Use for new pipelines. List - Generates a record with an indexed list with a map for header and value. Requires the use of delimited data functions to process data. Use only to maintain pipelines created before 1.1.0.
Lines to Skip	Number of lines to skip before reading data.
Parse NULLs	Replaces the specified string constant with null values.
NULL Constant	String constant to replace with null values.
Charset	Character encoding of the files to be processed.
Ignore Control Characters	Removes all ASCII control characters except for the tab, line feed, and carriage return characters.

For JSON data, on the Data Format tab, configure the following properties:


JSON Property	Description
JSON Content	Type of JSON content. Use one of the following options: JSON array of objects Multiple JSON objects
Max Object Length (chars)	Maximum number of characters in a JSON object. Longer objects are diverted to the pipeline for error handling. This property can be limited by the Data Collector parser buffer size. For more information, see Maximum Record Size.
Charset	Character encoding of the files to be processed.
Ignore Control Characters	Removes all ASCII control characters except for the tab, line feed, and carriage return characters.

For log data, on the Data Format tab, configure the following properties:


Log Property	Description
Log Format	Format of the log files. Use one of the following options: Common Log Format Combined Log Format Apache Error Log Format Apache Access Log Custom Format Regular Expression Grok Pattern Log4j Common Event Format (CEF) Log Event Extended Format (LEEF)
Max Line Length	Maximum length of a log line. The origin truncates longer lines. This property can be limited by the Data Collector parser buffer size. For more information, see Maximum Record Size.
Retain Original Line	Determines how to treat the original log line. Select to include the original log line as a field in the resulting record. By default, the original line is discarded.
Charset	Character encoding of the files to be processed.
Ignore Control Characters	Removes all ASCII control characters except for the tab, line feed, and carriage return characters.

When you select Apache Access Log Custom Format, use Apache log format strings to define the Custom Log Format.
When you select Regular Expression, enter the regular expression that describes the log format, and then map the fields that you want to include to each regular expression group.
When you select Grok Pattern, you can use the Grok Pattern Definition field to define custom grok patterns. You can define a pattern on each line.
In the Grok Pattern field, enter the pattern to use to parse the log. You can use a predefined grok patterns or create a custom grok pattern using patterns defined in Grok Pattern Definition.
For more information about defining grok patterns and supported grok patterns, see Defining Grok Patterns.

When you select Log4j, define the following properties:


Log4j Property	Description
On Parse Error	Determines how to handle information that cannot be parsed: Skip and Log Error - Skips reading the line and logs a stage error. Skip, No Error - Skips reading the line and does not log an error. Include as Stack Trace - Includes information that cannot be parsed as a stack trace to the previously-read log line. The information is added to the message field for the last valid log line.
Use Custom Log Format	Allows you to define a custom log format.
Custom Log4J Format	Use log4j variables to define a custom log format.

For protobuf data, on the Data Format tab, configure the following properties:


Protobuf Property	Description
Protobuf Descriptor File	Descriptor file (.desc) to use. The descriptor file must be in the Data Collector resources directory, `$SDC_RESOURCES`. For information about generating the descriptor file, see Protobuf Data Format Prerequisites. For more information about environment variables, see Java and Security Configuration.
Message Type	The fully-qualified name for the message type to use when reading data. Use the following format: `<package name>.<message type>`. Use a message type defined in the descriptor file.
Delimited Messages	Indicates if a message might include more than one protobuf message.

For text data, on the Data Format tab, configure the following properties:


Text Property	Description
Max Line Length	Maximum number of characters allowed for a line. Longer lines are truncated. Adds a boolean field to the record to indicate if it was truncated. The field name is Truncated. This property can be limited by the Data Collector parser buffer size. For more information, see Maximum Record Size.
Use Custom Delimiter	Uses custom delimiters to define records instead of line breaks.
Custom Delimiter	One or more characters to use to define records.
Include Custom Delimiter	Includes delimiter characters in the record.
Charset	Character encoding of the files to be processed.
Ignore Control Characters	Removes all ASCII control characters except for the tab, line feed, and carriage return characters.

For XML data, on the Data Format tab, configure the following properties:


XML Property	Description
Delimiter Element	Delimiter to use to generate records. Omit a delimiter to treat the entire XML document as one record. Use one of the following: An XML element directly under the root element. Use the XML element name without surrounding angle brackets ( < > ) . For example, msg instead of <msg>. A simplified XPath expression that specifies the data to use. Use a simplified XPath expression to access data deeper in the XML document or data that requires a more complex access method. For more information about valid syntax, see Simplified XPath Syntax.
Compression Format	The compression format of the files: None - Processes only uncompressed files. Compressed File - Processes files compressed by the supported compression formats. Archive - Processes files archived by the supported archive formats. Compressed Archive - Processes files archived and compressed by the supported archive and compression formats.
File Name Pattern within Compressed Directory	For archive and compressed archive files, file name pattern that represents the files to process within the compressed directory. You can use UNIX-style wildcards, such as an asterisk or question mark. For example, .json. Default is , which processes all files.
Preserve Root Element	Includes the root element in the generated records. When omitting a delimiter to generate a single record, the root element is the root element of the XML document. When specifying a delimiter to generate multiple records, the root element is the XML element specified as the delimiter element or is the last XML element in the simplified XPath expression specified as the delimiter element.
Include Field XPaths	Includes the XPath to each parsed XML element and XML attribute in field attributes. Also includes each namespace in an xmlns record header attribute. When not selected, this information is not included in the record. By default, the property is not selected.
Namespaces	Namespace prefix and URI to use when parsing the XML document. Define namespaces when the XML element being used includes a namespace prefix or when the XPath expression includes namespaces. For information about using namespaces with an XML element, see Using XML Elements with Namespaces. For information about using namespaces with XPath expressions, see Using XPath Expressions with Namespaces. Using simple or bulk edit mode, click the Add icon to add additional namespaces.
Output Field Attributes	Includes XML attributes and namespace declarations in the record as field attributes. When not selected, XML attributes and namespace declarations are included in the record as fields. By default, the property is not selected.
Max Record Length (chars)	The maximum number of characters in a record. Longer records are diverted to the pipeline for error handling. This property can be limited by the Data Collector parser buffer size. For more information, see Maximum Record Size.
Charset	Character encoding of the files to be processed.
Ignore Control Characters	Removes all ASCII control characters except for the tab, line feed, and carriage return characters.