Google Cloud Storage

The Google Cloud Storage origin reads objects stored in Google Cloud Storage. The objects must be fully written and reside in a single bucket. The object names must share a prefix pattern. For information about supported versions, see Supported Systems and Versions in the Data Collector documentation.

With the Google Cloud Storage origin, you define the bucket, prefix pattern, and optional common prefix. These properties determine the objects that the origin processes.

You also define the project ID and credentials to use when connecting to Google Cloud Storage. You can also use a connection to configure the origin.

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 Google Cloud Storage 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.

Note: The origin processes objects based on object names and locations. Having objects with the same name in the same location can cause the origin to skip reading the duplicate objects.

The origin can generate events for an event stream. For more information about dataflow triggers and the event framework, see Dataflow Triggers Overview.

Credentials

Before reading objects in Google Cloud Storage, the origin must pass credentials to Google Cloud Storage.

You can provide credentials using one the following options:

Google Cloud default credentials
Credentials in a file
Credentials in a stage property

For details on how to configure each option, see Security in Google Cloud Stages.

Common Prefix, Prefix Pattern, and Wildcards

The Google Cloud Storage 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/ and all nested prefixes, you can use the following common prefix and prefix pattern:

Common Prefix: US/East/MD/
Prefix Pattern: **/*.log

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:

Common Prefix: US/
Prefix Pattern: **/weblogs/*.log

Common Prefix: 
Prefix Pattern: US/**/weblogs/*.log

Record Header Attributes

When the Google Cloud Storage origin processes Parquet data and Skip Union Indexes is not enabled, it generates an avro.union.typeIndex./id record header attribute identifying the index number of the element in a union the data is read from.

Event Generation

The Google Cloud Storage origin can generate events when it completes processing all available data and the configured batch wait time has elapsed.

Google Cloud Storage events can be used in any logical way. For example:

With the Google Cloud Storage executor to perform tasks after writing an object or whole file.
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 Stopping a Pipeline After Processing All Available Data.
With a destination to store event information.
For an example, see Preserving an Audit Trail of Events.

For more information about dataflow triggers and the event framework, see Dataflow Triggers Overview.

Event Records

Event records generated by the Google Cloud Storage 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 type: no-more-data - Generated after the origin completes processing all available objects and the number of seconds configured for Batch Wait Time has elapsed.
sdc.event.version	Integer that indicates the version of the event record type.
sdc.event.creation_timestamp	Epoch timestamp when the stage created the event.

The Google Cloud Storage origin can generate the following event record:

no-more-data

The Google Cloud Storage 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.

Data Formats

The Google Cloud Storage 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.

The stage 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 file.
In Pipeline Configuration - Use the schema that you provide in the stage configuration properties.
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 stage to look up the schema in 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 Confluent Schema Registry overrides any schema that might be included in the file and can improve performance.

The stage reads files compressed by Avro-supported compression codecs without requiring additional configuration. To enable the stage to read files compressed by other codecs, use the compression format property in the stage.

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.

Excel

Generates a record for every row in the file. Can process .xls or .xlsx files.

You can configure the origin to read from all sheets in a workbook or from particular sheets in a workbook. You can specify whether files include a header row and whether to ignore the header row. You can also configure the origin to skip cells that do not have a corresponding header value. A header row must be the first row of a file. Vertical header columns are not recognized.

The origin cannot process Excel files with large numbers of rows. You can save such files as CSV files in Excel, and then use the origin to process with the delimited data format.

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.

Parquet

The origin generates records for every Parquet record in the file. The file must contain the Parquet schema. The origin uses the Parquet schema to generate records.

The stage includes the Parquet schema in a parquetSchema record header attribute.

When Skip Union Indexes is not enabled, the origin generates an avro.union.typeIndex./id record header attribute identifying the index number of the element in the union that the data is read from. If a schema contains many unions and the pipeline does not depend on index information, you can enable Skip Union Indexes to avoid long processing times associated with storing a large number of indexes.

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.

Configuring a Google Cloud Storage Origin

Configure a Google Cloud Storage origin to read data from objects in Google Cloud Storage.

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: Discard - Discards the record. Send to Error - Sends the record to the pipeline for error handling. Stop Pipeline - Stops the pipeline.

On the GCS tab, configure the following properties:


GCS Property	Description
Bucket	Bucket that contains the objects to be read. Note: The bucket name must be DNS compliant. For more information about bucket naming conventions, see the Google Cloud Storage documentation.
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.
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.
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 Number of Retries	Maximum number of times to retry the connection when the connection fails. Default is 10.
Retry Interval (ms)	Time between retries in milliseconds. Default is 10,000.

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: Avro Binary Delimited Excel JSON Log Parquet Protobuf SDC Record Text Whole File

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 file. 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. For more information about credential stores, see Credential Stores in the Data Collector documentation.
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. Overrides any existing schema definitions associated with the data.
Schema Subject	Avro schema subject to look up in 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 Confluent Schema Registry.

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


Binary Property	Description
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.
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
Header Line	Indicates whether a file contains a header line, and whether to use the header line.
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.
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 Line Delimiter	Characters that delimit lines or records. Default is the newline character (\n). Available when using the Apache Commons parser with the multi-character delimiter format.
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.
Field Separator	One or more characters to use as delimiter characters between columns. Available when using the Univocity parser.
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.
Line Separator	Line separator. Available when using the Univocity parser.
Allow Comments	Allows commented data to be ignored for custom delimiter format. Available when using the Univocity parser.
Comment Character	Character that marks a comment when comments are enabled for custom delimiter format. 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.
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 Excel files, on the Data Format tab, configure the following properties:


Excel Property	Description
Excel Header Option	Indicates whether files include a header row and whether to ignore the header row. A header row must be the first row of a file.
Skip Cells With No Header	Skips processing cells when they do not have a corresponding header value. Available when Excel Header Option is set to With Header Line.
Include Cells With Empty Value	Includes empty cells in records.
Read All Sheets	Reads all sheets in the Excel file.
Import Sheets	Name of sheet to read. Using simple or bulk edit mode, click Add Another to add additional sheets. Available when Read All Sheets is not selected.

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
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.
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)
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.
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 Parquet data, on the Data Format tab, configure the following property:


Parquet Property	Description
Skip Union Indexes	Omits header attributes identifying the index number of the element in a union that data is read from. If a schema contains many unions and the pipeline does not depend on index information, you can enable this property to avoid long processing times associated with storing a large number of indexes.

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 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.
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.

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: 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.

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


Text Property	Description
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.
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 whole files, on the Data Format tab, configure the following properties:


Whole File Property	Description
Verify Checksum	Verifies the checksum during the read.
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.

On the Credentials tab, configure the following properties:


Credentials 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.
Project ID	Google Cloud project ID to use.
Credentials Provider	Provider for Google Cloud credentials: Default credentials provider - Uses Google Cloud default credentials. Service account credentials file (JSON) - Uses credentials stored in a JSON service account credentials file. Service account credentials (JSON) - Uses JSON-formatted credentials information from a service account credentials file.
Credentials File Path (JSON)	Path to the Google Cloud service account credentials file used to connect. The credentials file must be a JSON file. Enter a path relative to the Data Collector resources directory, `$SDC_RESOURCES`, or enter an absolute path.
Credentials File Content (JSON)	Contents of a Google Cloud service account credentials JSON file used to connect. Enter JSON-formatted credential information in plain text, or use an expression to call the information from runtime resources or a credential store. For more information about credential stores, see Credential Stores in the Data Collector documentation.

On the Error Handling tab, configure the following properties:


Error Handling Property	Description
Error Handling Option	Action taken when an error occurs while processing an object: None - Keeps the object in place. Archive - Copies or moves the object to another prefix or bucket. Delete - Deletes the object. Note: When processing whole file data, you can archive by copying the object. Moving or deleting the object is not supported.
Archiving Option	Action taken 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	Action taken after successfully processing an object: None - Keep the object in place. Archive - Copy or move the object to another location. Delete - Delete the object.
Archiving Option	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.