{"objects":[{"metadata":{"identifier":{"packageName":"Matillion Exchange","name":"MongoDB Incremental Load","revision":1,"type":"DYNAMIC"},"rootJobReference":{"name":"MongoDB - 1 - Iterate Objects","type":"ORCHESTRATION","parameterMetadata":[{"slot":2,"variableName":"user_name","variableType":"SCALAR","displayName":"Username","description":"The username to be supplied to connect to the source.","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":false},{"slot":3,"variableName":"password_manager_entry","variableType":"SCALAR","displayName":"Password Manager Entry","description":"The name in the Matillion Password Manager for the password relating to the authentication method.","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":false},{"slot":4,"variableName":"connection_url","variableType":"SCALAR","displayName":"Server","description":"The server IP or DNS address of the MongoDB server endpoint.","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":true},{"slot":5,"variableName":"database_name","variableType":"SCALAR","displayName":"Database Name","description":"Name of MongoDB database to load data from","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":true},{"slot":6,"variableName":"flatten_objects","variableType":"SCALAR","displayName":"Flatten Objects","description":"Yes: Nested document structures are flattened into a set of fields. Determining which fields are available can become expensive in this mode, since more data needs to be scanned in order to determine which fields are available.\nNo: Nested document structures are returns as JSON strings. They can be further queried/manipulated by JSON functions in a transformation job after being staged","defaultValue":[{"values":{"1":"Yes"}}],"defaultValueType":"TEXT","required":true},{"slot":7,"variableName":"flatten_arrays","variableType":"SCALAR","displayName":"Flatten Arrays","description":"\"The maximum number of elements that any array can be flattened to. Flattened arrays have each element placed into its own respective (newly created) column.\nEntering 0 for this property will ensure all arrays remain in JSON string format.\nEntering -1 for this property will ensure all elements from arrays are flattened.\nRequesting to flatten more elements than exist in an array will result in all elements of that array being flattened.\n\nDetermining which fields are available can become expensive in this mode, since more data needs to be scanned in order to determine which fields are available.\"","defaultValue":[{"values":{"1":"0"}}],"defaultValueType":"TEXT","required":true},{"slot":8,"variableName":"source_list","variableType":"GRID","displayName":"Tables And Columns","description":"Contains the list of tables and columns (and in some cases an incremental_column to specify which column the load should be incremented on [accepts values of 0 or 1]) to be processed. ","defaultValue":[{"values":{"1":""}}],"defaultValueType":null,"required":true},{"slot":9,"variableName":"advanced_connection_options","variableType":"GRID","displayName":"Connection Options","description":"A list of values and parameters. Parameters and their allowed values are database/driver specific. Referring to the data model will provide insight of what you could provide here.\n
\nThey are usually not required as sensible defaults are assumed.","defaultValue":[{"values":{"1":""}}],"defaultValueType":null,"required":false},{"slot":10,"variableName":"load_concurrent","variableType":"SCALAR","displayName":"Load Type","description":"Sequential - Iterations are done in sequence, waiting for each to complete before starting the next. \nThis is the default.\n
\nConcurrent - Iterations are run concurrently. This requires all \"Variables to Iterate\" to be defined as\nCopied variables, so that each iteration gets its own copy of the variable isolated from the same\nvariable being used by other concurrent executions.\n
Note: The maximum concurrency is limited by the number of available threads (2x the number of virtual cpus on your cloud instance).","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":true},{"slot":11,"variableName":"stage_warehouse","variableType":"SCALAR","displayName":"Stage Warehouse","description":"The warehouse name where the staging data will be stored.","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":true},{"slot":12,"variableName":"stage_database","variableType":"SCALAR","displayName":"Stage Database","description":"The database name where the staging data will be stored.","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":true},{"slot":13,"variableName":"stage_schema","variableType":"SCALAR","displayName":"Stage Schema","description":"The schema name where the staging data will be stored.","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":true},{"slot":14,"variableName":"stage_prefix","variableType":"SCALAR","displayName":"Stage Prefix","description":"A prefix value that will be added to the start of the stage table names.\n
\ne.g. If a Stage Prefix of 'stage_' is specified and the table being processed is named 'test_data' then the target table will be named 'stage_test_data'.","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":true},{"slot":15,"variableName":"target_warehouse","variableType":"SCALAR","displayName":"Target Warehouse","description":"The warehouse name where the target data will be stored.","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":true},{"slot":16,"variableName":"target_database","variableType":"SCALAR","displayName":"Target Database","description":"The database name where the target data will be stored.","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":true},{"slot":17,"variableName":"target_schema","variableType":"SCALAR","displayName":"Target Schema","description":"The schema name where the target data will be stored.","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":true},{"slot":18,"variableName":"target_prefix","variableType":"SCALAR","displayName":"Target Prefix","description":"A prefix value that will be added to the start of the target table names.\n
\ne.g. If a Target Prefix of 'target_' is specified and the table being processed is named 'test_data' then the target table will be named 'target_test_data'.","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":false},{"slot":19,"variableName":"staging_type","variableType":"SCALAR","displayName":"Staging","description":"(AWS Only) Snowflake Managed: Allow Matillion ETL to create and use a temporary internal stage on Snowflake for staging the data. This stage, along with the staged data, will cease to exist after loading is complete.
\n Existing Amazon S3 Location: Selecting this will avail the user of properties to specify a custom staging area on S3.","defaultValue":[{"values":{"1":"Snowflake Managed"}}],"defaultValueType":"TEXT","required":false},{"slot":20,"variableName":"s3_bucket_name","variableType":"SCALAR","displayName":"S3 Bucket Name","description":"(AWS Only) The name of an S3 bucket for temporary storage. Ensure your access credentials have S3 access and permission to write to the bucket. See this document for details on setting up access. The temporary objects created in this bucket will be removed again after the load completes, they are not kept.
\nThis property is available when using an Existing Amazon S3 Location for Staging.","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":false},{"slot":21,"variableName":"encryption_method","variableType":"SCALAR","displayName":"Encryption","description":"(AWS Only) Decide on how the files are encrypted inside the S3 Bucket.This property is available when using an Existing Amazon S3 Location for Staging.
\n None: No encryption.
\n SSE KMS: Encrypt the data according to a key stored on KMS.
\n SSE S3: Encrypt the data according to a key stored on an S3 bucket","defaultValue":[{"values":{"1":"None"}}],"defaultValueType":"TEXT","required":false},{"slot":22,"variableName":"kms_key_id","variableType":"SCALAR","displayName":"KMS Key ID","description":"The ID of the KMS encryption key you have chosen to use in the 'Encryption' property.","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":false},{"slot":23,"variableName":"storage_account","variableType":"SCALAR","displayName":"Azure Storage Account","description":"(Azure Only) Azure Storage Account to allow Matillion ETL to specify a blob container object on Snowflake for staging data. ","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":false},{"slot":24,"variableName":"blob_container","variableType":"SCALAR","displayName":"Azure Blob Container","description":"(Azure Only) Azure Blob Container to allow Matillion ETL to use the blob storage container object on Snowflake for staging data. ","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":false},{"slot":25,"variableName":"log_metrics","variableType":"SCALAR","displayName":"Log Metrics","description":"Option to switch off Metrics logging in the full product - default is TRUE which records the metrics for the batch run. ","defaultValue":[{"values":{"1":"TRUE"}}],"defaultValueType":"TEXT","required":false}]},"orchestrationJobs":["MongoDB - 1 - Iterate Objects","MongoDB - 4 - Query Source","MongoDB - 3 - Stage Object","MongoDB - 2 - Stage Object"],"transformationJobs":[],"imageMetadata":{"componentIcon":"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","smallIcon":"iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAABL0lEQVR42mNgoCUIWepb4jnJk50szRGrA+pDlvn/95zjtaahoYGJNM1r/M0jVgT8C4UYAMTeJaQZsCpgc8TKgP8wAzzmeH10menCT5Tm0FWhPEDbf4ENWA5zAQh7JhHvfKBmDANmey0kyoDw1QGe2AwAemM7cQasCDLF6oI5nsurq6stKisrzfEakDYzjRWo+S2GC2Z75VVUVGwF4r1APLOkpIQbbxpAjgXvWT7/CmuL08rKyniBrpCvqqoyKi8v78RpgOc2T3agAaeilwWDDYjpi5kDtDUDWQ2QvxivV+LWBQo3LMs6EzYvsBCYEoWAfl8KFGasqalRBtFAfh7BAF26qC151apVzCA20Mn+QLwWiO8BNdsTFSOrFnXI/f//nxFJiBFoQEVhYSEn1XIsAIy/tTcU2bOmAAAAAElFTkSuQmCC"},"description":"","helpHtml":"
Property | Type | Description |
---|---|---|
Username | Variable | The username to be supplied to connect to the source. |
Password Manager Entry | Variable | The name in the Matillion Password Manager for the password relating to the authentication method. |
Server | Variable | The server IP or DNS address of the MongoDB server endpoint. |
Database Name | Variable | Name of MongoDB database to load data from |
Flatten Objects | Variable | Yes: Nested document structures are flattened into a set of fields. Determining which fields are available can become expensive in this mode, since more data needs to be scanned in order to determine which fields are available.\nNo: Nested document structures are returns as JSON strings. They can be further queried/manipulated by JSON functions in a transformation job after being staged |
Flatten Arrays | Variable | \"The maximum number of elements that any array can be flattened to. Flattened arrays have each element placed into its own respective (newly created) column.\nEntering 0 for this property will ensure all arrays remain in JSON string format.\nEntering -1 for this property will ensure all elements from arrays are flattened.\nRequesting to flatten more elements than exist in an array will result in all elements of that array being flattened.\n\nDetermining which fields are available can become expensive in this mode, since more data needs to be scanned in order to determine which fields are available.\" |
Tables And Columns | Grid | Contains the list of tables and columns (and in some cases an incremental_column to specify which column the load should be incremented on [accepts values of 0 or 1]) to be processed. |
Connection Options | Grid | A list of values and parameters. Parameters and their allowed values are database/driver specific. Referring to the data model will provide insight of what you could provide here.\n \nThey are usually not required as sensible defaults are assumed. |
Load Type | Variable | Sequential - Iterations are done in sequence, waiting for each to complete before starting the next. \nThis is the default.\n \nConcurrent - Iterations are run concurrently. This requires all \"Variables to Iterate\" to be defined as\nCopied variables, so that each iteration gets its own copy of the variable isolated from the same\nvariable being used by other concurrent executions.\n Note: The maximum concurrency is limited by the number of available threads (2x the number of virtual cpus on your cloud instance). |
Stage Warehouse | Variable | The warehouse name where the staging data will be stored. |
Stage Database | Variable | The database name where the staging data will be stored. |
Stage Schema | Variable | The schema name where the staging data will be stored. |
Stage Prefix | Variable | A prefix value that will be added to the start of the stage table names.\n \ne.g. If a Stage Prefix of 'stage_' is specified and the table being processed is named 'test_data' then the target table will be named 'stage_test_data'. |
Target Warehouse | Variable | The warehouse name where the target data will be stored. |
Target Database | Variable | The database name where the target data will be stored. |
Target Schema | Variable | The schema name where the target data will be stored. |
Target Prefix | Variable | A prefix value that will be added to the start of the target table names.\n \ne.g. If a Target Prefix of 'target_' is specified and the table being processed is named 'test_data' then the target table will be named 'target_test_data'. |
Staging | Variable | (AWS Only) Snowflake Managed: Allow Matillion ETL to create and use a temporary internal stage on Snowflake for staging the data. This stage, along with the staged data, will cease to exist after loading is complete. \n Existing Amazon S3 Location: Selecting this will avail the user of properties to specify a custom staging area on S3. |
S3 Bucket Name | Variable | (AWS Only) The name of an S3 bucket for temporary storage. Ensure your access credentials have S3 access and permission to write to the bucket. See this document for details on setting up access. The temporary objects created in this bucket will be removed again after the load completes, they are not kept. \nThis property is available when using an Existing Amazon S3 Location for Staging. |
Encryption | Variable | (AWS Only) Decide on how the files are encrypted inside the S3 Bucket.This property is available when using an Existing Amazon S3 Location for Staging. \n None: No encryption. \n SSE KMS: Encrypt the data according to a key stored on KMS. \n SSE S3: Encrypt the data according to a key stored on an S3 bucket |
KMS Key ID | Variable | The ID of the KMS encryption key you have chosen to use in the 'Encryption' property. |
Azure Storage Account | Variable | (Azure Only) Azure Storage Account to allow Matillion ETL to specify a blob container object on Snowflake for staging data. |
Azure Blob Container | Variable | (Azure Only) Azure Blob Container to allow Matillion ETL to use the blob storage container object on Snowflake for staging data. |
Log Metrics | Variable | Option to switch off Metrics logging in the full product - default is TRUE which records the metrics for the batch run. |