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Stage Number | Stage | Category | Summary | Environment | Iterations | Estimated Person Time | Estimated Computer Time |
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1 | Import and parse reference dataset (Optional) | Parsing | This optional step in the Bulk Loader process is to cross check an address for a match in a reference data set. If a source address is found in the reference dataset the address makes it to the next step. If not found the address is put aside in an exclusion set for later review. | Once per Bulk Loader process | 1 hour | 10 minutes | |
2 | Import, parse and filter source dataset | Parsing | Import the dataset destined for the EAS. Parse and filter the set. | Once per Bulk Loader process | 90 minutes | 15 minutes | |
Geocode and filter | Geocoding | Geocode the set and filter further based on geocoder score and status. | ArcMap | Once per Bulk Loader process | 1 hour | 5 minutes | |
4 | Export full set (single batch) or subset (multiple batches) | Geocoding | For large datasets, create one of many subsets that will be run through the Bulk Loader in many batches. | ArcMap | One or more batches for each Bulk Loader process | 30 minutes per batch | 5 minutes per batch |
5 | Bulk Load batch (full set or subset) | Bulk Loading | Run each subset batch through the Bulk Loader. | One or more batches for each Bulk Loader process | 1 hour per batch | 5 minutes per batch | |
6 | Extract results | Bulk Loading | Extract and archive the list of addresses that were added to the EAS . Also archive the unique EAS 'change request id' associated with this batch. Also archive the addresses that were rejected by the Bulk Loader in this batch. | PostgreSQL / pgAdmin | One or more batches for each Bulk Loader process | 1 hour per batch | 5 minutes per batch |
7 | Cleanup and Restoration | Bulk Loading | Clean up database, restore services and in the event of a failure, restore from backup. | One or more batches for each Bulk Loader process |
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This optional stage is run once per Bulk Loader process. This stage can be skipped if the reference dataset is already available or if the optional 'filter by reference' step is skipped.
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- Script Name (*) csv2pg.py
- URL https://bitbucket.org/sfgovdt/sfgis-general-address-parser/src/master/csv2pg.py
- Important arguments
- input_file - The relative path to the raw CSV file.
- output_table - The name of the table for the imported records.
- Example usage
Import CSV file into PostgreSQL table (++<odbc>)
Code Block language bashtext firstline 1 title csv2pg linenumbers true python csv2pg.py --odbc_server=<odbc-server> -- Name or IP address of the database server, e.g. localhost --odbc_port=<odbc-port> -- Port of the database server, e.g. 5432 --odbc_database=<odbc-database> -- Name of the database, e.g. awgdb --odbc_uid=<odbc-uid> -- Database user name --odbc_pwd=<odbc-pwd> -- Database user password --input_file=./path/to/raw_reference_file.csv --output_table=reference_raw
- Output table
- This step generates a new table. The name of the new table is passed as a required command line argument.
- Output fields
- All columns in the input CSV file are imported as fields in the new table.
- sfgisgapid: a new serial, not null, primary key
- Artifacts (**)
- reference_raw.csv - The input CSV table serves as the artifact for this step.
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- Script Name (*) csv2pg.py
- URL https://bitbucket.org/sfgovdt/sfgis-general-address-parser/src/master/csv2pg.py
- Important arguments
- input_file: The relative path to the raw CSV file.
- output_table: The name of the table for the imported records.
- Example usage
Import CSV file into PostgreSQL table (++<odbc>)
Code Block language text firstline 1 title csv2pg linenumbers true python csv2pg.py \ --odbc_server=<odbc-server> \ --odbc_port=<odbc-port> \ --odbc_database=<odbc-database> \ --odbc_uid=<odbc-uid> \ --odbc_pwd=<odbc-pwd> \ --input_file=./path/to/raw_source_file.csv \ --output_table=addresses_raw
- Output table
- This step generates a new table. The name of the new table is passed as a required command line argument.
- Output fields
- All columns in the input CSV file are imported as fields in the new table.
- sfgisgapid: a new serial, not null, primary key
- Artifacts (**)
- addresses_raw.csv - The input CSV table serves as the artifact for this step.
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Anchorstage3 stage3
Stage 3 - Geocode and filter
stage3 | |
stage3 |
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Step 3.1 - Geocode source dataset
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Anchorstage4 stage4
Stage 4 - Export full set (single batch) or subset (multiple batches)
stage4 | |
stage4 |
Note | ||
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Stages 4, 5 and 6 can be run one time with the results from Stage 3, or they can be run in multiple batches of subsets. A major consideration of when to run the full set at once versus in batches is the number of records being Bulk Loaded. The size of each Bulk Loader operation affects the following aspects of the EAS:
For medium-to-large datasets (input sets with over 1000 records) it is recommended to run the process on a development server and assess the implications of the operation. Where appropriate, perform the Bulk Loading process in batches over several days or weeks. The remaining steps will document one example iteration of a multi-batch process. |
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Anchorstage5 stage5
Stage 5 - Run the Bulk Loader
stage5 | |
stage5 |
For a complete set of steps and background about the Bulk Loader, see also Running the Bulk Loader, a page dedicated to its input, operation and results.
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Anchorstage6 stage6
Stage 6 - Extract results
stage6 | |
stage6 |
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Step 6.1 - Archive exceptions
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- If the Bulk Loader Process was run on the production server then restore services
Turn on production-to-replication service
- TODO: add steps
Turn on downstream database propagation service(s)
Resume downstream replication to internal business system database (SF PROD WEB).
Code Block language text firstline 1 title start xmit sudo /var/www/html/eas/bin/xmit_change_notifications.bsh start
Enable front-end access to EAS
Place the Web servers into live mode (SF PROD WEB, DR PROD WEB).
Code Block language bash linenumbers true cd /var/www/html sudo ./set_eas_mode.sh LIVE
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