{"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","description":"The Database name on the MongoDB server.","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<br>\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<br>\nConcurrent - Iterations are run concurrently. This requires all \"Variables to Iterate\" to be defined as\n<a href=\"https://redshiftsupport.matillion.com/customer/portal/articles/2037630?b_id=8915#header1\" target=\"_blank\"><i>Copied</i> variables</a>, so that each iteration gets its own copy of the variable isolated from the same\nvariable being used by other concurrent executions.\n<span class=\"env rs sf\"><br><b>Note:</b> The maximum concurrency is limited by the number of available threads (2x the number of virtual cpus on your cloud instance).</span>","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":true},{"slot":11,"variableName":"s3_bucket_name","variableType":"SCALAR","displayName":"S3 Bucket Name","description":"<span class=\"env sf\">(AWS Only) </span>The name of an S3 bucket for temporary storage. Ensure your access credentials have S3 access and permission to write to the bucket. See <a href=\"https://redshiftsupport.matillion.com/customer/portal/articles/2054760\" target=\"_blank\">this document</a> 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.<br>\n<span class=\"env sf\">This property is available when using an Existing Amazon S3 Location for Staging.</span>","defaultValue":[{"values":{"1":""}}],"defaultValueType":"TEXT","required":true},{"slot":12,"variableName":"dist_style","variableType":"SCALAR","displayName":"Distribution Style","description":"<b>Even:</b> Distributes rows around the Redshift cluster evenly.<br>\n<b>All:</b> Copy rows to all nodes in the Redshift cluster.<br>\nTable distribution is critical to good performance. See the <a href=\"http://docs.aws.amazon.com/redshift/latest/dg/tutorial-tuning-tables-distribution.html\" target=\"_blank\">Amazon Redshift</a> documentation for more information.","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<br>\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_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":16,"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<br>\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":17,"variableName":"encryption_method","variableType":"SCALAR","displayName":"Encryption","description":"<span class=\"env sf\">(AWS Only) </span>Decide on how the files are encrypted inside the S3 Bucket.<span class=\"env sf\">This property is available when using an Existing Amazon S3 Location for Staging.</span><br>\n                <b>None:</b> No encryption.<br>\n                <b>SSE KMS:</b> Encrypt the data according to a key stored on <a href=\"https://aws.amazon.com/kms/\" target=\"_blank\">KMS</a>.<br>\n                <b>SSE S3:</b> Encrypt the data according to a key stored on an <a href=\"http://docs.aws.amazon.com/AmazonS3/latest/dev/UsingServerSideEncryption.html\" target=\"_blank\">S3 bucket</a>","defaultValue":[{"values":{"1":"None"}}],"defaultValueType":"TEXT","required":false},{"slot":18,"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":19,"variableName":"log_metrics","variableType":"SCALAR","displayName":"log_metrics","description":"","defaultValue":[{"values":{"1":"TRUE"}}],"defaultValueType":"TEXT","required":true}]},"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":"<div class=\"mtln\"><img src=\"data:image/png;base64,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\"><h3>MongoDB Incremental Load</h3><p style='white-space: pre-line; word-wrap: break-word;'></p><h3>Properties</h3><table><tbody><tr><th>Property</th><th>Type</th><th>Description</th></tr><tr><td>Username</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'>The username to be supplied to connect to the source.</td></tr><tr><td>Password Manager Entry</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'>The name in the Matillion Password Manager for the password relating to the authentication method.</td></tr><tr><td>Server</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'>The server IP or DNS address of the MongoDB server endpoint.</td></tr><tr><td>Database</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'>The Database name on the MongoDB server.</td></tr><tr><td>Flatten Objects</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'>\"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\"</td></tr><tr><td>Flatten Arrays</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'>\"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.\"</td></tr><tr><td>Tables and Columns</td><td>Grid</td><td style='white-space: pre-line; word-wrap: break-word;'>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. </td></tr><tr><td>Connection Options</td><td>Grid</td><td style='white-space: pre-line; word-wrap: break-word;'>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<br>\nThey are usually not required as sensible defaults are assumed.</td></tr><tr><td>Load Type</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'>Sequential - Iterations are done in sequence, waiting for each to complete before starting the next. \nThis is the default.\n<br>\nConcurrent - Iterations are run concurrently. This requires all \"Variables to Iterate\" to be defined as\n<a href=\"https://redshiftsupport.matillion.com/customer/portal/articles/2037630?b_id=8915#header1\" target=\"_blank\"><i>Copied</i> variables</a>, so that each iteration gets its own copy of the variable isolated from the same\nvariable being used by other concurrent executions.\n<span class=\"env rs sf\"><br><b>Note:</b> The maximum concurrency is limited by the number of available threads (2x the number of virtual cpus on your cloud instance).</span></td></tr><tr><td>S3 Bucket Name</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'><span class=\"env sf\">(AWS Only) </span>The name of an S3 bucket for temporary storage. Ensure your access credentials have S3 access and permission to write to the bucket. See <a href=\"https://redshiftsupport.matillion.com/customer/portal/articles/2054760\" target=\"_blank\">this document</a> 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.<br>\n<span class=\"env sf\">This property is available when using an Existing Amazon S3 Location for Staging.</span></td></tr><tr><td>Distribution Style</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'><b>Even:</b> Distributes rows around the Redshift cluster evenly.<br>\n<b>All:</b> Copy rows to all nodes in the Redshift cluster.<br>\nTable distribution is critical to good performance. See the <a href=\"http://docs.aws.amazon.com/redshift/latest/dg/tutorial-tuning-tables-distribution.html\" target=\"_blank\">Amazon Redshift</a> documentation for more information.</td></tr><tr><td>Stage Schema</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'>The schema name where the staging data will be stored.</td></tr><tr><td>Stage Prefix</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'>A prefix value that will be added to the start of the stage table names.\n<br>\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'.</td></tr><tr><td>Target Schema</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'>The schema name where the target data will be stored.</td></tr><tr><td>Target Prefix</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'>A prefix value that will be added to the start of the target table names.\n<br>\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'.</td></tr><tr><td>Encryption</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'><span class=\"env sf\">(AWS Only) </span>Decide on how the files are encrypted inside the S3 Bucket.<span class=\"env sf\">This property is available when using an Existing Amazon S3 Location for Staging.</span><br>\n                <b>None:</b> No encryption.<br>\n                <b>SSE KMS:</b> Encrypt the data according to a key stored on <a href=\"https://aws.amazon.com/kms/\" target=\"_blank\">KMS</a>.<br>\n                <b>SSE S3:</b> Encrypt the data according to a key stored on an <a href=\"http://docs.aws.amazon.com/AmazonS3/latest/dev/UsingServerSideEncryption.html\" target=\"_blank\">S3 bucket</a></td></tr><tr><td>KMS Key ID</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'>The ID of the KMS encryption key you have chosen to use in the 'Encryption' property.</td></tr><tr><td>log_metrics</td><td>Variable</td><td style='white-space: pre-line; word-wrap: break-word;'></td></tr></tbody></table></div>","created":1613563277072},"orchestrationJobs":{"MongoDB - 1 - Iterate Objects":{"id":-2,"revision":18,"created":1613563013623,"timestamp":1613563013623,"components":{"788":{"id":788,"inputCardinality":"ONE","outputCardinality":"MANY","connectorHint":"SUCCESS_FAIL","executionHint":"EXECUTE","implementationID":-1773186960,"x":-240,"y":16,"width":32,"height":32,"inputConnectorIDs":[15154],"outputSuccessConnectorIDs":[796],"outputFailureConnectorIDs":[],"outputUnconditionalConnectorIDs":[],"outputTrueConnectorIDs":[],"outputFalseConnectorIDs":[],"exportMappings":{},"parameters":{"1":{"slot":1,"name":"Name","elements":{"1":{"slot":1,"values":{"1":{"slot":1,"type":"STRING","value":"Get unique table names"}}}},"visible":true,"status":{},"columnNames":[]},"2":{"slot":2,"name":"Script","elements":{"1":{"slot":1,"values":{"1":{"slot":1,"type":"STRING","value":"source_list = context.getGridVariable('source_list')\n\n# get distinct list of table names from source_list\ndistinct_table_names = list(set([table for table, col, inc_col, key_col in source_list]))\n\n# convert to list of lists to store in grid variable\ndistinct_table_names = [[name] for name in sorted(distinct_table_names)]\ncontext.updateGridVariable(\"distinct_table_names\", distinct_table_names)\n\nprint(f\"source_list: {str(source_list)}\")\nprint(f\"distinct_table_names: {str(distinct_table_names)}\")\n"}}}},"visible":true,"status":{},"columnNames":[]},"3":{"slot":3,"name":"Interpreter","elements":{"1":{"slot":1,"values":{"1":{"slot":1,"type":"STRING","value":"Python 3"}}}},"visible":true,"status":{},"columnNames":[]},"4":{"slot":4,"name":"Timeout","elements":{"1":{"slot":1,"values":{"1":{"slot":1,"type":"INTEGER","value":"360"}}}},"visible":true,"status":{},"columnNames":[]}},"validationStatus":{},"status":{},"expectedFailure":null,"activationStatus":"ENABLED","outputIterationConnectorIDs":[],"inputIterationConnectorIDs":[]},"789":{"id":789,"inputCardinality":"ONE","outputCardinality":"MANY","connectorHint":"SUCCESS_FAIL","executionHint":"EXECUTE","implementationID":-1773186960,"x":-32,"y":16,"width":32,"height":32,"inputConnectorIDs":[796],"outputSuccessConnectorIDs":[795],"outputFailureConnectorIDs":[],"outputUnconditionalConnectorIDs":[],"outputTrueConnectorIDs":[],"outputFalseConnectorIDs":[],"exportMappings":{},"parameters":{"1":{"slot":1,"name":"Name","elements":{"1":{"slot":1,"values":{"1":{"slot":1,"type":"STRING","value":"Update Environment Default"}}}},"visible":true,"status":{},"columnNames":[]},"2":{"slot":2,"name":"Script","elements":{"1":{"slot":1,"values":{"1":{"slot":1,"type":"STRING","value":"# Script to replace any [Environment Default] entries with the schema name\n\nif target_platform == 'Redshift':\n  \n    if stage_schema == '[Environment Default]':\n        context.updateVariable('stage_schema', environment_default_schema)\n  \n    if target_schema == '[Environment Default]':\n        context.updateVariable('target_schema', environment_default_schema)\n\nelif target_platform == 'Snowflake':\n    \n    if stage_schema == '[Environment Default]':\n        context.updateVariable('stage_schema', environment_default_schema)\n  \n    if target_schema == '[Environment Default]':\n        context.updateVariable('target_schema', environment_default_schema)\n\n    if stage_database == '[Environment Default]':\n        context.updateVariable('stage_database', environment_database)\n\n    if target_database == '[Environment Default]':\n        context.updateVariable('target_database', environment_database)\n  \nelif target_platform == 'BigQuery':\n  \n    if stage_dataset == '[Environment Default]':\n        context.updateVariable('stage_dataset', environment_default_schema)\n\n    if target_dataset == '[Environment Default]':\n        context.updateVariable('target_dataset', environment_default_schema)\n\n    if stage_project == '[Environment Default]':\n        context.updateVariable('stage_project', environment_database)\n\n    if target_project == '[Environment Default]':\n        context.updateVariable('target_project', environment_database)\n"}}}},"visible":true,"status":{},"columnNames":[]},"3":{"slot":3,"name":"Interpreter","elements":{"1":{"slot":1,"values":{"1":{"slot":1,"type":"STRING","value":"Python 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