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Table of Contents
Overview

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Stage NumberStageCategorySummaryEnvironmentIterationsEstimated Person TimeEstimated Computer Time
1Import and parse reference dataset (Optional)ParsingThis 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.

Python 3

PostgreSQL / pgAdmin

Once per Bulk Loader process1 hour10 minutes
2Import, parse and filter source datasetParsingImport the dataset destined for the EAS. Parse and filter the set.

Python 3

PostgreSQL / pgAdmin

Once per Bulk Loader process90 minutes15 minutes

3

Geocode and filterGeocodingGeocode the set and filter further based on geocoder score and status.ArcMapOnce per Bulk Loader process1 hour 5 minutes
4Export full set (single batch) or subset (multiple batches)GeocodingFor large datasets, create one of many subsets that will be run through the Bulk Loader in many batches.ArcMapOne or more batches for each Bulk Loader process30 minutes per batch5 minutes per batch
5Bulk Load batch (full set or subset)Bulk LoadingRun each subset batch through the Bulk Loader.

EAS <environment>(+)

PostgreSQL / pgAdmin

One or more batches for each Bulk Loader process1 hour per batch5 minutes per batch
6Extract resultsBulk LoadingExtract 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 / pgAdminOne or more batches for each Bulk Loader process1 hour per batch5 minutes per batch
7Cleanup and RestorationBulk LoadingClean 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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stage1
stage1
Stage 1 Import and parse reference dataset (Optional)

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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  1. Script Name (*) csv2pg.py
  2. URL https://bitbucket.org/sfgovdt/sfgis-general-address-parser/src/master/csv2pg.py
  3. Important arguments
    1. input_file - The relative path to the raw CSV file.
    2. output_table - The name of the table for the imported records.
  4. Example usage
    1. Import CSV file into PostgreSQL table (++<odbc>)

      Code Block
      languagetextbash
      firstline1
      titlecsv2pg
      linenumberstrue
      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


  5. Output table
    1. This step generates a new table. The name of the new table is passed as a required command line argument.
  6. Output fields
    1. All columns in the input CSV file are imported as fields in the new table.
    2. sfgisgapid: a new serial, not null, primary key
  7. Artifacts (**)
    1. reference_raw.csv - The input CSV table serves as the artifact for this step.

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stage3
stage3
Stage 3 
Geocode and filter

  •  

    Step 3.1 - Geocode source dataset

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stage4
stage4
Stage 4 
Export full set (single batch) or subset (multiple batches)

Note
titleA Note about Batches

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:

  • The disk space consumed by the database server
  • The EAS user interface section that lists addresses loaded in a given Bulk Loader operation
  • The weekly email attachment listing new addresses added to 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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stage5
stage5
Stage 5 
Run the Bulk Loader

(info) 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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stage6
stage6
Stage 6 
Extract results

  •  

    Step 6.1 - Archive exceptions

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  1. If the Bulk Loader Process was run on the production server then restore services
    1. Turn on production-to-replication service
      • TODO: add steps
    2. Turn on downstream database propagation service(s)
      • Resume downstream replication to internal business system database (SF PROD WEB).

        Code Block
        languagetext
        firstline1
        titlestart xmit
        sudo /var/www/html/eas/bin/xmit_change_notifications.bsh start


    3. Enable front-end access to EAS
      • Place the Web servers into live mode (SF PROD WEB, DR PROD WEB).

        Code Block
        languagebash
        linenumberstrue
        cd /var/www/html
        sudo ./set_eas_mode.sh LIVE


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