1.Amazon S3
The Amazon S3 origin reads objects stored in Amazon S3. The object names must share a prefix pattern and should be fully written. To read messages from Amazon SQS, use the Amazon SQS Consumer origin.
With the Amazon S3 origin, you define the region, bucket, prefix pattern, optional common prefix, and read order. These properties determine the objects that the origin processes. You can optionally include Amazon S3 object metadata in the record as record header attributes.
After processing an object or upon encountering errors, the origin can keep, archive, or delete the object. When archiving, the origin can copy or move the object.
When the pipeline stops, the Amazon S3 origin notes where it stops reading. When the pipeline starts again, the origin continues processing from where it stopped by default. You can reset the origin to process all requested objects.
You can configure the origin to decrypt data stored on Amazon S3 with server-side encryption and customer-provided encryption keys. You can optionally use a proxy to connect to Amazon S3.
The origin can generate events for an event stream. For more information about dataflow triggers and the event framework, see Dataflow Triggers Overview.
1.1.AWS Credentials
When Data Collector reads data from an Amazon S3 origin, it must pass credentials to Amazon Web Services.
Use one of the following methods to pass AWS credentials:
IAM roles
When Data Collector runs on an Amazon EC2 instance, you can use the AWS Management Console to configure an IAM role for the EC2 instance. Data Collector uses the IAM instance profile credentials to automatically connect to AWS.
When you use IAM roles, you do not need to specify the Access Key ID and Secret Access Key properties in the origin.
For more information about assigning an IAM role to an EC2 instance, see the Amazon EC2 documentation.
AWS access key pairs
When Data Collector does not run on an Amazon EC2 instance or when the EC2 instance doesn’t have an IAM role, you must specify the Access Key ID and Secret Access Key properties in the origin.
Tip: To secure sensitive information such as access key pairs, you can use runtime resources or credential stores. For more information about credential stores, see Credential Stores in the Data Collector documentation.
1.2.Common Prefix, Prefix Pattern, and Wildcards
The Amazon S3 origin appends the common prefix to the prefix pattern to define the objects that the origin processes. You can specify an exact prefix pattern or you can use Ant-style path patterns to read multiple objects recursively.
Ant-style path patterns can include the following wildcards:
- Question mark (?) to match a single character
- Asterisk (*) to match zero or more characters
- Double asterisks (**) to match zero or more directories
For example, to process all log files in US/East/MD/
If the unnamed nested prefixes that you want to include appear earlier in the hierarchy, such as US/**/weblogs/, you can include the nested prefixes in the prefix pattern or define the entire hierarchy in the prefix pattern, as follows:
1.3.Record Header Attributes
When the Amazon S3 origin processes Avro data, it includes the Avro schema in an avroSchema record header attribute. You can also configure the origin to include Amazon S3 object metadata in record header attributes.
You can use the record:attribute or record:attributeOrDefault functions to access the information in the attributes. For more information about working with record header attributes, see Working with Header Attributes.
Object Metadata in Record Header Attributes
You can include Amazon S3 object metadata in record header attributes. Include metadata when you want to use the information to help process records. For example, you might include metadata if you want to route records to different branches of a pipeline based on the last-modified timestamp.
Use the Include Metadata property to include metadata in the record header attributes. When you include metadata in record header attributes, the Amazon S3 origin includes the following information:
System-defined metadata
The origin includes the following system-defined metadata:
- Name - The object name. Bucket and prefix information is included as follows:
- Cache-Control
- Content-Disposition
- Content-Encoding
- Content-Length
- Content-MD5
- Content-Range
- Content-Type
- ETag
- Expires
- Last-Modified
For more information about Amazon S3 system-defined metadata, see the Amazon S3 documentation.
User-defined metadata
When available, the Amazon S3 origin also includes user-defined metadata in record header attributes.
Amazon S3 requires user-defined metadata to be named with the following prefix: x-amz-meta-.
When generating the record header attribute, the origin omits the prefix.
For example, if you have user-defined metadata called "x-amz-meta-extraInfo", the origin names the record header attribute as follows: extraInfo.
For more information about record header attributes, see Record Header Attributes.
1.4.Read Order
The Amazon S3 origin reads objects in ascending order based on the object key name or the last modified timestamp. For best performance when reading a large number of objects, configure the origin to read objects based on the key name.
You can configure one of the following read orders:
Lexicographically Ascending Key Names
The Amazon S3 origin can read objects in lexicographically ascending order based on key names. Note that lexicographically ascending order reads the numbers 1 through 11 as follows:
For example, you configure the Amazon S3 origin to read from the following bucket, common prefix, and prefix pattern using lexicographically ascending order based on key names:
The origin reads the following objects in the following order:
To read these objects in logical and lexicographically ascending order, you might add leading zeros to the file naming convention as follows:
Last Modified Timestamp
The Amazon S3 origin can read objects in ascending order based on the last modified timestamp. When you start a pipeline, the origin starts processing data with the earliest object that matches the common prefix and prefix pattern, and then progresses in chronological order. If two or more objects have the same timestamp, the origin processes the objects in lexicographically increasing order by key name.
To process objects that include a timestamp earlier than processed objects, reset the origin to read all available objects.
For example, you configure the origin to read from the ServerEast bucket, using LogFiles/ as the common prefix and *.log
The origin reads these objects in order of the timestamp, as follows:
If a new object arrives with a timestamp of 04-29-2016 12:00:00, the Amazon S3 origin does not process the object unless you reset the origin.
1.5.Buffer Limit and Error Handling
The Amazon S3 origin uses a buffer to read objects into memory to produce records. The size of the buffer determines the maximum size of the record that can be processed.
The buffer limit helps prevent out of memory errors. Decrease the buffer limit when memory on the Data Collector machine is limited. Increase the buffer limit to process larger records when memory is available.
When a record is larger than the specified limit, the origin processes the object based on the stage error handling:
Discard
The origin discards the record and all remaining records in the object, and then continues processing the next object.
Send to Error
With a buffer limit error, the origin cannot send the record to the pipeline for error handling because it is unable to fully process the record.
Instead, the origin displays a message indicating that a buffer overrun error occurred in the pipeline history.
If an error directory is configured for the stage, the origin moves the object to the error directory and continues processing the next object.
Stop Pipeline
The origin stops the pipeline and displays a message indicating that a buffer overrun error occurred. The message includes the object and offset where the buffer overrun error occurred. The information displays in the pipeline history.
Note: You can also check the Data Collector log file for error details.
1.6.Server Side Encryption
You can configure the origin to decrypt data stored on Amazon S3 with Amazon Web Services server-side encryption.
When configured for server-side encryption, the origin uses customer-provided encryption keys to decrypt the data. To use server-side encryption, provide the following information:
- Base64 encoded 256-bit encryption key
- Base64 encoded 128-bit MD5 digest of the encryption key using RFC 1321
For information about implementing customer-provided encryption keys in the origin system, see the Amazon S3 documentation.
1.7.Event Generation
The Amazon S3 origin can generate events when it completes processing all available data and the configured batch wait time has elapsed.
Amazon S3 events can be used in any logical way. For example:
- With the Pipeline Finisher executor to stop the pipeline and transition the pipeline to a Finished state when the origin completes processing available data.
When you restart a pipeline stopped by the Pipeline Finisher executor, the origin continues processing from the last-saved offset unless you reset the origin.
For an example, see Case Study: Stop the Pipeline.
- With a destination to store event information.
For an example, see Case Study: Event Storage.
For more information about dataflow triggers and the event framework, see Dataflow Triggers Overview.
Event Records
Event records generated by the Amazon S3 origin have the following event-related record header attributes. Record header attributes are stored as String values:
Record Header Attribute | Description |
sdc.event.type | Event type. Uses the following event type:
|
sdc.event.version | An integer that indicates the version of the event record type. |
sdc.event.creation_timestamp | Epoch timestamp when the stage created the event. |
The Amazon S3 origin can generate the following event record:
no-more-data
The Amazon S3 origin generates a no-more-data event record when the origin completes processing all available records and the number of seconds configured for Batch Wait Time elapses without any new objects appearing to be processed.
No-more-data event records generated by the origin have the sdc.event.type set to no-more-data and include the following fields:
Event Record Field | Description |
record-count | Number of records successfully generated since the pipeline started or since the last no-more-data event was created. |
error-count | Number of error records generated since the pipeline started or since the last no-more-data event was created. |
file-count | Number of objects that the origin attempted to process. Can include objects that were unable to be processed or were not fully processed. |
1.8.Data Formats
The Amazon S3 origin processes data differently based on the data format. The origin processes the following types of data:
Avro
Generates a record for every Avro record. Includes a "precision" and "scale" field attribute for each Decimal field. For more information about field attributes, see Field Attributes.
The origin writes the Avro schema to an avroSchema record header attribute. For more information about record header attributes, see Record Header Attributes.
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 file.
- In Pipeline Configuration - Use the schema that you provide in the stage configuration.
- Confluent Schema Registry - Retrieve the schema from Confluent Schema Registry. The Confluent Schema Registry is a distributed storage layer for Avro schemas. You can configure the origin to look up the schema in the Confluent Schema Registry by the schema ID or subject specified in the stage configuration.
Using a schema in the stage configuration or retrieving a schema from the Confluent Schema Registry overrides any schema that might be included in the file and can improve performance.
The origin reads files compressed by Avro-supported compression codecs without requiring additional configuration. To enable the origin to read files compressed by other codecs, use the compression format property in the stage.
Delimited
Generates a record for each delimited line. You can use the following delimited format types:
- 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.
- Postgres CSV - Postgres comma-separated file.
- Postgres Text - Postgres text file.
- Tab-Separated Values - File that includes tab-separated values.
- Custom - File that uses user-defined delimiter, escape, and quote characters.
You can use a list or list-map root field type for delimited data, optionally including the header information when available. For more information about the root field types, see Delimited Data Root Field Type.
When using a header line, you can allow processing records with additional columns. The additional columns are named using a custom prefix and integers in sequential increasing order, such as _extra_1, _extra_2. When you disallow additional columns when using a header line, records that include additional columns are sent to error.
You can also replace a string constant with null values.
When a record exceeds the user-defined maximum record length, the origin cannot continue processing data in the file. Records already processed from the file are passed to the pipeline. The behavior of the origin is then based on the error handling configured for the stage:
- Discard - The origin continues processing with the next file, leaving the partially-processed file in the directory.
- To Error - The origin continues processing with the next file. If a post-processing error directory is configured for the stage, the origin moves the partially-processed file to the error directory. Otherwise, it leaves the file in the directory.
- Stop Pipeline - The origin stops the pipeline.
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 cannot continue processing data in the file. Records already processed from the file are passed to the pipeline. The behavior of the origin is then based on the error handling configured for the stage:
- Discard - The origin continues processing with the next file, leaving the partially-processed file in the directory.
- To Error - The origin continues processing with the next file. If a post-processing error directory is configured for the stage, the origin moves the partially-processed file to the error directory. Otherwise, it leaves the file in the directory.
- Stop Pipeline - The origin stops the pipeline.
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.
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 file. The origin handles the file based on file error handling properties and continues reading the next file.
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.
Whole File
Streams whole files from the origin system to the destination system. You can specify a transfer rate or use all available resources to perform the transfer.
The origin uses checksums to verify the integrity of data transmission.
The origin generates two fields: one for a file reference and one for file information. For more information, see Whole File Data Format.
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.
Note: Field attributes and record header attributes are written to destination systems automatically only when you use the SDC RPC data format in destinations. For more information about working with field attributes and record header attributes, and how to include them in records, see Field Attributes and Record Header Attributes.
When a record exceeds the user-defined maximum record length, the origin cannot continue processing data in the file. Records already processed from the file are passed to the pipeline. The behavior of the origin is then based on the error handling configured for the stage:
- Discard - The origin continues processing with the next file, leaving the partially-processed file in the directory.
- To Error - The origin continues processing with the next file. If a post-processing error directory is configured for the stage, the origin moves the partially-processed file to the error directory. Otherwise, it leaves the file in the directory.
- Stop Pipeline - The origin stops the pipeline.
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.
1.9.Configuring an Amazon S3 Origin
Configure an Amazon S3 origin to read data from objects in Amazon S3.
- In the Properties panel, on the General tab, configure the following properties:
General Property | Description |
Name | Stage name. |
Description | Optional description. |
Produce Events | Generates event records when events occur. Use for event handling. |
On Record Error | Error record handling for the stage:
|
- On the Amazon S3 tab, configure the following properties:
Amazon S3 Property | Description |
Access Key ID | AWS access key ID. Required when not using IAM roles with IAM instance profile credentials. |
Secret Access Key | AWS secret access key. Required when not using IAM roles with IAM instance profile credentials. |
Region | Amazon S3 region. |
Endpoint | Endpoint to connect to when you select Other for the region. Enter the endpoint name. |
Bucket | Bucket that contains the objects to be read. |
Common Prefix | Optional common prefix that describes the location of the objects. When defined, the common prefix acts as a root for the prefix pattern. |
Delimiter | Delimiter used by Amazon S3 to define the prefix hierarchy. Default is slash ( / ). |
Include Metadata | Includes system-defined and user-defined metadata in record header attributes. |
Prefix Pattern | Prefix pattern that describes the objects to be processed. You can include the entire path to the objects. You can also use Ant-style path patterns to read objects recursively. |
Read Order | The order to use when reading objects:
For best performance when reading a large number of objects, use lexicographical order based on key names. |
File Pool Size | Maximum number of files that the origin stores in memory for processing after loading and sorting all files present on S3. Increasing this number can improve pipeline performance when Data Collector resources permit. Default is 100. |
Buffer Limit (KB) | Maximum buffer size. The buffer size determines the size of the record that can be processed. Decrease when memory on the Data Collector machine is limited. Increase to process larger records when memory is available. Default is 128 KB. |
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. |
Batch Wait Time (ms) | Number of milliseconds to wait before sending a partial or empty batch. |
- To use server-side encryption, on the SSE tab, configure the following properties:
SSE Property | Description |
Use Server-Side Encryption | Enables the use of server-side encryption. |
Customer Encryption Key | A Base64 encoded 256-bit encryption key. |
Customer Encryption Key MD5 | A Base64 encoded 128-bit MD5 digest of the encryption key using RFC 1321. |
- On the Error Handling tab, configure the following properties:
Error Handling Property | Description |
Error Handling Option | The action taken when an error occurs while processing an object:
When archiving processed objects, best practice is to also archive objects that cannot be processed. |
Archiving Option | The action to take when archiving an object that cannot be processed. You can copy or move the object to another prefix or bucket. When you use another prefix, enter the prefix. When you use another bucket, enter a prefix and bucket. Copying the object leaves the original object in place. |
Error Prefix | Prefix for the objects that cannot be processed. |
Error Bucket | Bucket for the objects that cannot be processed. |
- On the Post Processing tab, configure the following properties:
Post Processing Property | Description |
Post Processing Option | The action taken after successfully processing an object:
|
Archiving Option | The action to take when archiving a processed object. You can copy or move the object to another prefix or bucket. When you use another prefix, enter the prefix. When you use another bucket, enter a prefix and bucket. Copying the object leaves the original object in place. |
Post Process Prefix | Prefix for processed objects. |
Post Process Bucket | Bucket for processed objects. |
- On the Advanced tab, optionally configure proxy information:
Advanced Property | Description |
Connection Timeout | Seconds to wait for a response before closing the connection. Default is 10 seconds. |
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 usernames and passwords, you can use runtime resources or credential stores. For more information about credential stores, see Credential Stores in the Data Collector documentation. |
- On the Data Format tab, configure the following property:
Data Format Property | Description |
Data Format | Data format for source files. Use one of the following formats:
|
- 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:
Using a schema in the stage configuration or in the 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 use 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. Use the following format to enter the URL: |
Lookup Schema By | Method used to look up the schema in the Confluent Schema Registry:
Overrides any existing schema definitions associated with the data. |
Schema Subject | Avro schema subject to look up in the Confluent Schema Registry. If the specified subject has multiple schema versions, the origin 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 the Confluent Schema Registry. |
- For delimited data, on the Data Format tab, configure the following properties:
Delimited Property | Description |
Compression Format | The compression format of the files:
|
File Name Pattern within Compressed Directory | 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. |
Delimiter Format Type | Delimiter format type. Use one of the following options:
|
Header Line | Indicates whether a file contains a header line, and whether to use the header line. |
Allow Extra Columns | When processing data with a header line, allows processing records with more columns than exist in the 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_. |
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. |
Delimiter Character | Delimiter character for a custom delimiter format. 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 ( | ). |
Escape Character | Escape character for a custom file type. |
Quote Character | Quote character for a custom file type. |
Root Field Type | Root field type to use:
|
Lines to Skip | 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 Ctrl Characters | Removes all ASCII control characters except for the tab, line feed, and carriage return characters. |
10. For JSON data, on the Data Format tab, configure the following properties:
JSON Property | Description |
Compression Format | The compression format of the files:
|
File Name Pattern within Compressed Directory | 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. |
JSON Content | Type of JSON content. Use one of the following options:
|
Maximum 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 Ctrl Characters | Removes all ASCII control characters except for the tab, line feed, and carriage return characters. |
11. For log data, on the Data Format tab, configure the following properties:
Log Property | Description |
Compression Format | The compression format of the files:
|
File Name Pattern within Compressed Directory | 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. |
Log Format | Format of the log files. Use one of the following options:
|
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 Ctrl 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:
|
Use Custom Log Format | Allows you to define a custom log format. |
Custom Format | Use log4j variables to define a custom log format. |
12. For protobuf data, on the Data Format tab, configure the following properties:
Protobuf Property | Description |
Compression Format | The compression format of the files:
|
File Name Pattern within Compressed Directory | 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. |
Protobuf Descriptor File | Descriptor file (.desc) to use. The descriptor file must be in the Data Collector resources directory, $SDC_RESOURCES. For more information about environment variables, see Data Collector Environment Configuration in the Data Collector documentation. For information about generating the descriptor file, see Protobuf Data Format Prerequisites. |
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 file might include more than one protobuf message. |
13. For SDC Record data, on the Data Format tab, configure the following properties:
SDC Record Property | Description |
Compression Format | The compression format of the files:
|
File Name Pattern within Compressed Directory | 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. |
14. For text data, on the Data Format tab, configure the following properties:
Text Property | Description |
Compression Format | The compression format of the files:
|
File Name Pattern within Compressed Directory | 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. |
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 Ctrl Characters | Removes all ASCII control characters except for the tab, line feed, and carriage return characters. |
15. For whole files, on the Data Format tab, configure the following properties:
Whole File Property | Description |
Buffer Size (bytes) | Size of the buffer to use to transfer data. |
Rate per Second | Transfer rate to use. Enter a number to specify a rate in bytes per second. Use an expression to specify a rate that uses a different unit of measure per second, e.g. ${5 * MB}. Use -1 to opt out of this property. By default, the origin does not use a transfer rate. |
Verify Checksum | Verifies the checksum during the read. |
16. For XML data, on the XML tab, configure the following properties:
XML Property | Description |
Compression Format | The compression format of the files:
|
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:
Use the XML element name without surrounding angle brackets ( < > ) . For example, msg instead of <msg>.
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. |
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. Note: Field attributes and record header attributes are written to destination systems automatically only when you use the SDC RPC data format in destinations. For more information about working with field attributes and record header attributes, and how to include them in records, see Field Attributes and Record Header Attributes. |
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. Note: Field attributes are automatically included in records written to destination systems only when you use the SDC RPC data format in the destination. For more information about working with field attributes, see Field Attributes. 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 Ctrl Characters | Removes all ASCII control characters except for the tab, line feed, and carriage return characters. |
2.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.
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 can use IAM roles or AWS access key pairs to access the data.
You can optionally include Amazon SQS message attributes and sender attributes in records as record header attributes.
2.1.AWS Credentials
When Data Collector reads data from an Amazon SQS Consumer origin, it must pass credentials to Amazon Simple Queue Services.
Use one of the following methods to pass AWS credentials:
IAM roles
When Data Collector runs on an Amazon EC2 instance, you can use the AWS Management Console to configure an IAM role for the EC2 instance. Data Collector uses the IAM instance profile credentials to automatically connect to AWS.
When you use IAM roles, you do not need to specify the Access Key ID and Secret Access Key properties in the origin.
For more information about assigning an IAM role to an EC2 instance, see the Amazon EC2 documentation.
AWS access key pairs
When Data Collector does not run on an Amazon EC2 instance or when the EC2 instance doesn’t have an IAM role, you must specify the Access Key ID and Secret Access Key properties in the origin.
Tip: To secure sensitive information such as access key pairs, you can use runtime resources or credential stores. For more information about credential stores, see Credential Stores in the Data Collector documentation.
2.2.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:
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.
2.3.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
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.
2.4.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:
|
All Attributes | Includes the standard SQS attributes listed above and the following additional SQS attributes:
|
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.
2.5.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. For more information about field attributes, see Field Attributes.
The origin writes the Avro schema to an avroSchema record header attribute. For more information about record header attributes, see Record Header Attributes.
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. The Confluent Schema Registry is a distributed storage layer for Avro schemas. You can configure the origin to look up the schema in the 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 the 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. You can use the following delimited format types:
- 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.
- Postgres CSV - Postgres comma-separated file.
- Postgres Text - Postgres text file.
- Tab-Separated Values - File that includes tab-separated values.
- Custom - File that uses user-defined delimiter, escape, and quote characters.
You can use a list or list-map root field type for delimited data, optionally including the header information when available. For more information about the root field types, see Delimited Data Root Field Type.
When using a header line, you can allow processing records with additional columns. The additional columns are named using a custom prefix and integers in sequential increasing order, such as _extra_1, _extra_2. When you disallow additional columns when using a header line, records that include additional columns are sent to error.
You can also replace a string constant with null values.
When a record exceeds the maximum record length defined for the origin, the origin processes the object based on the error handling configured for the stage.
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.
Note: Field attributes and record header attributes are written to destination systems automatically only when you use the SDC RPC data format in destinations. For more information about working with field attributes and record header attributes, and how to include them in records, see Field Attributes and Record Header Attributes.
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.
2.6.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:
|
- On the SQS tab, configure the following properties:
SQS Property | Description |
Access Key ID | AWS access key ID. Required when not using IAM roles with IAM instance profile credentials. |
Secret Access Key | AWS secret access key. Required when not using IAM roles with IAM instance profile credentials. |
Region | Amazon SQS region. |
Queue Name Prefix | The common prefix for the queues to process. Wildcards are not allowed. |
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. |
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:
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. Default is 10 seconds. |
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 usernames and passwords, you can use runtime resources or credential stores. For more information about credential stores, see Credential Stores in the Data Collector documentation. |
- 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:
|
- 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:
Using a schema in the stage configuration or in the 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 use 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. Use the following format to enter the URL: |
Lookup Schema By | Method used to look up the schema in the Confluent Schema Registry:
Overrides any existing schema definitions associated with the message. |
Schema Subject | Avro schema subject to look up in the Confluent Schema Registry. If the specified subject has multiple schema versions, the origin 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 the 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:
|
Header Line | Indicates whether a file contains a header line, and whether to use the header line. |
Allow Extra Columns | When processing data with a header line, allows processing records with more columns than exist in the 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_. |
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. |
Delimiter Character | Delimiter character for a custom delimiter format. 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 ( | ). |
Escape Character | Escape character for a custom file type. |
Quote Character | Quote character for a custom file type. |
Root Field Type | Root field type to use:
|
Lines to Skip | 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 Ctrl 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:
|
Maximum 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 Ctrl 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:
|
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 Ctrl 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:
|
Use Custom Log Format | Allows you to define a custom log format. |
Custom Format | Use log4j variables to define a custom log format. |
10. 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 Data Collector Environment Configuration in the Data Collector documentation. |
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. |
11. 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 Ctrl Characters | Removes all ASCII control characters except for the tab, line feed, and carriage return characters. |
12. 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:
Use the XML element name without surrounding angle brackets ( < > ) . For example, msg instead of <msg>.
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. |
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. Note: Field attributes and record header attributes are written to destination systems automatically only when you use the SDC RPC data format in destinations. For more information about working with field attributes and record header attributes, and how to include them in records, see Field Attributes and Record Header Attributes. |
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. Note: Field attributes are automatically included in records written to destination systems only when you use the SDC RPC data format in the destination. For more information about working with field attributes, see Field Attributes. 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 Ctrl Characters | Removes all ASCII control characters except for the tab, line feed, and carriage return characters. |
3. Azure IoT/Event Hub Consumer
The Azure IoT/Event Hub Consumer origin reads data from Microsoft Azure Event Hub. The origin can use multiple threads to enable parallel processing of data from a single Azure event hub.
Before you use the Azure IoT/Event Hub Consumer origin, make sure you have the required Microsoft Azure storage account and container.
When you configure the Azure IoT/Event Hub Consumer, you specify the Microsoft Azure namespace and event hub names. You also define the shared access policy name and connection string key. You specify the consumer group to use and an event processor prefix that the origin uses when communicating with Azure Event Hub.
You configure the storage account details, such as the storage account name and key. And you specify the number of threads to use during processing.
3.1.Storage Account and Container Prerequisite
Before you use the Azure IoT/Event Hub Consumer origin, you need a Microsoft Azure storage account and at least one container.
The origin stores offsets in a storage account container, so to ensure the integrity of offset information, you must use a different container for each pipeline that includes an Azure IoT/Event Hub Consumer origin.
For example, say you use the Azure IoT/Event Hub Consumer as the origin for an IoT pipeline and a Transactions pipeline. To keep the offset data for these pipelines separate, you need to use two different storage account containers. They can be in the same storage account or in different storage accounts. When you configure the origins, you specify the storage account and container to use.
To create a new container for the pipeline:
- Log into the Microsoft Azure portal: https://portal.azure.com
- In the Navigation panel, click Storage Accounts.
- Select the storage account to use.
If you need to create a storage account, click the Add icon. Enter a name for the storage account, and enter or select a resource group name. You can use the defaults for all other properties.
- In the storage account view, click + Container to create a container.
- Enter a container name, and click OK.
Tip: Use a name that can be easily identified as the container for the pipeline that you want to use it in.
If these steps are no longer accurate, see the Microsoft Azure Event Hub documentation.
3.2.Resetting the Origin in Event Hub
You cannot use Data Collector to reset the origin for Azure IoT/Event Hub Consumer pipelines because the offset is stored in Azure Event Hub.
To reset the origin in Microsoft Azure Event Hub:
- In the Microsoft Azure portal, navigate to the storage account.
- To delete the offset information stored for the pipeline, delete the container that the pipeline uses.
This can take some time. Allow the portal to complete the removal of the container before continuing.
- To enable the pipeline to store new offset information when you restart the pipeline, create a new container with the same name. Or, use a different name and update the Container Name property in the pipeline.
3.3.Multithreaded Processing
The Azure IoT/Event Hub Consumer origin performs parallel processing and enables the creation of a multithreaded pipeline.
The Azure IoT/Event Hub Consumer origin uses multiple concurrent threads to read from an event hub based on the Max Threads property. When you start the pipeline, the origin creates the number of threads specified in the Max Threads property. Each thread connects to the origin system and creates a batch of data, and passes the batch to an available pipeline runner.
A pipeline runner is a sourceless pipeline instance
Multithreaded pipelines preserve the order of records within each batch, just like a single-threaded pipeline. But since batches are processed by different pipeline instances, the order that batches are written to destinations is not ensured.
For example, say you set the Max Threads property to 5. When you start the pipeline, the origin creates five threads, and Data Collector creates a matching number of pipeline runners. Upon receiving data, the origin passes a batch to each of the pipeline runners for processing.
Each pipeline runner performs the processing associated with the rest of the pipeline. After a batch is written to pipeline destinations, the pipeline runner becomes available for another batch of data. Each batch is processed and written as quickly as possible, independent from other batches processed by other pipeline runners, so batches may be written differently from the read-order.
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.
3.4.Data Formats
The Azure IoT/Event Hub Consumer origin reads data from Microsoft Azure Event Hub based on the data format that you select. You can use the following data formats:
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.
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.
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.
3.5.Configuring an Azure IoT/Event Hub Consumer
Configure an Azure IoT/Event Hub Consumer origin to write data to Microsoft Azure Event Hub. Be sure to complete the necessary prerequisites before you configure the origin.
- 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:
|
- On the Event Hub tab, configure the following properties:
Event Hub Property | Description |
Namespace Name | The name of the namespace that contains the event hub that you want to use. |
Event Hub Name | The event hub name. |
Shared Access Policy Name | The policy name associated with the namespace. To retrieve the policy name, when logged into the Azure portal, navigate to your namespace and event hub, and then click Shared Access Policies for a list of policies. When appropriate, you can use the default shared access key policy, RootManageSharedAccessKey. |
Connection String Key | One of the connection string keys associated with the specified shared access policy. To retrieve a connection string key, after accessing the list of shared access policies, click the policy name, and then copy the Connection String - Primary Key value. The value typically begins with "Endpoint". |
Consumer Group | Consumer group to use. Enter a consumer group associated with the specified event hub. You can use the default consumer group, $Default. To view a list of available consumer groups, when viewing the event hub in the Azure portal, click Consumer Groups. |
Event Processor Prefix | A prefix to identify the pipeline. Use a different prefix for each pipeline that includes the origin. Used to communicate with Azure Event Hub. |
Storage Account Name | Name of the storage account to use. For information about creating a storage account, see Storage Account and Container Prerequisite. |
Storage Account Key | One of the keys for the storage account. To retrieve the storage account key, when viewing the storage account details in the Azure portal, click Access Keys. Then copy one of the default key values. |
Container Name | The name of the container to use for the pipeline. For information about creating a container, see Storage Account and Container Prerequisite. |
Max Threads | Number of threads the origin generates and uses for multithreaded processing. |
- On the Data Format tab, configure the following property:
Data Format Property | Description |
Data Format | Format of data to be written. Use one of the following options:
|
- For binary data, on the Data Format tab, configure the following properties:
Binary Property | Description |
Compression Format | The compression format of the files:
|
File Name Pattern within Compressed Directory | 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. |
Max Data Size (bytes) | Maximum number of bytes in the message. Larger messages cannot be processed or written to error. |
- For JSON data, on the Data Format tab, configure the following properties:
JSON Property | Description |
Compression Format | The compression format of the files:
|
File Name Pattern within Compressed Directory | 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. |
JSON Content | Type of JSON content. Use one of the following options:
|
Maximum 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 Ctrl Characters | Removes all ASCII control characters except for the tab, line feed, and carriage return characters. |
- For text data, on the Data Format tab, configure the following properties:
Text Property | Description |
Compression Format | The compression format of the files:
|
File Name Pattern within Compressed Directory | 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. |
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 Ctrl Characters | Removes all ASCII control characters except for the tab, line feed, and carriage return characters. |
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