{"id":174521,"date":"2011-02-09T20:29:34","date_gmt":"2011-02-10T04:29:34","guid":{"rendered":"http:\/\/www.esri.com\/arcgis-blog\/?post_type=blog&p=174521"},"modified":"2018-12-18T11:29:11","modified_gmt":"2018-12-18T19:29:11","slug":"improving-batch-geocoding-performance","status":"publish","type":"blog","link":"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-desktop\/analytics\/improving-batch-geocoding-performance","title":{"rendered":"Improving batch geocoding performance"},"author":3961,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","format":"standard","meta":{"_acf_changed":false,"_searchwp_excluded":""},"categories":[23341,23851],"tags":[25091,30211,24321,34501,30321],"industry":[],"product":[36991],"class_list":["post-174521","blog","type-blog","status-publish","format-standard","hentry","category-analytics","category-data-management","tag-geocoding","tag-geocoding-locator","tag-geoprocessing","tag-locators","tag-performance","product-arcgis-desktop"],"acf":{"short_description":"Geocoding performance has always been a top priority when working with large volumes of addresses, and it\u2019s a primary consideration","flexible_content":[{"acf_fc_layout":"content","content":"

Geocoding performance has always been a top priority when working with large volumes of addresses, and it\u2019s a primary consideration when designing and implementing a geocoding workflow.\u00a0 There are several factors that contribute to geocoding performance, I won\u2019t cover all of these in this article but, let\u2019s look at some simple, high value changes we can make to our locators and workflow to improve performance.<\/p>\n

Increasing the run time memory limit:<\/strong><\/p>\n

ArcGIS Locators can be configured to use more system memory.\u00a0 Using system memory (RAM) to work with locators is much faster than reading a locator from disk.\u00a0 ArcGIS supports use of 2GB memory on a 32 bit system and 3GB of memory on a 64 bit system.\u00a0 By default ArcGIS locators are configured to use 512MB of system memory.\u00a0 The default values were chosen to ensure the greatest possible system coverage, without exceeding system limits and possibly destabilizing a system.\u00a0 By increasing the memory allocation for locator use above 512MB we see good performance gains.<\/p>\n

ArcGIS locators support a \u201cRun Time Memory Limit\u201d parameter.\u00a0 For large geocoding jobs working against a large locator such as US streets, or US Composite, we\u2019ll want to set this limit near the capabilities of our system.\u00a0 With ArcGIS 10, geocoding performance continues improving as the cache grows beyond 2GB.<\/p>\n

Follow the steps below to create or edit an existing Run Time Memory Limit parameter:<\/p>\n

    \n
  1. Open the *.loc file in a text editor (note this is the .loc file and not the .loc.xml file).<\/li>\n
  2. Look for the line that starts with\u00a0RuntimeMemoryLimit =<\/em><\/i><\/li>\n
  3. If the value does not exist, create one\u00a0and change the value to represent the number of bytes of system memory you want to allocate for the locator:
    \n\u00a0 RuntimeMemoryLimit = 2048000000<\/em><\/i>\u00a0\u00a0<\/em><\/i><\/li>\n
  4. Save the locator.<\/li>\n
  5. Use the locator and compare performance and system memory use.<\/li>\n<\/ol>\n

    You can play with this value to find something that is appropriate for your system.\u00a0 In most cases you will see optimum performance near 2GB of memory.\u00a0 If you\u2019ve allocated too much memory, the system may become unstable or ArcGIS may crash.\u00a0 Reduce the memory allocation to rectify.<\/p>\n

    Presort reference data for optimal performance:<\/strong><\/p>\n

    It\u2019s always much faster to find something when it is organized than when it is chaotic.\u00a0\u00a0 Geocoding is no different.\u00a0 Sorted addresses can be geocoded faster than unsorted data.\u00a0 Sorted addresses tax the system less, hard disks don\u2019t have to work so hard and the geocoding engine makes less frequent memory allocations.<\/p>\n

    A typical approach for sorting data would be to sort by the highest level of geography first and then to sort on smaller levels of geography.\u00a0 With a U.S. address for example, you should sort the address data by State, followed by City, and Postal Code.\u00a0 If your data isn\u2019t already sorted, you can sort it using the ArcGIS Sort (Data Management) tool or you can configure a locator to sort data as it\u2019s read into the geocoding process.<\/p>\n

    Configuring a locator for sorting is similar to changing the run time memory limit, except you need to configure two parameters instead of one.\u00a0 The first parameter specifies the fields to sort by.\u00a0 These fields are the input fields defined by the locator.\u00a0 The second parameter is the number of records to sort in each process.\u00a0 You could sort the entire table, but that would be very memory and CPU intensive so instead you can choose to sort the first n number of records.\u00a0 Defining a higher value can help produce higher performance but again, taxes system resources.\u00a0 A typical value supporting good performance might be 100000 records.<\/p>\n

    Follow the steps below to create or edit an existing Batch\u00a0Presort parameter:<\/p>\n

    \n

      \n
    1. Open the *.loc file in a text editor (note this is the .loc file and not the .loc.xml file) .<\/li>\n
    2. Look for the line that starts with\u00a0BatchPresortInputs = State<\/em><\/i><\/li>\n
    3. \u00a0If the value does not exist, create one and assign the first locator input field to sort by. Repeat the entry for additional fields
      \nBatchPresortInputs = State
      \nBatchPresortInputs = City<\/em><\/i>
      \nBatchPresortInputs = Zip<\/em><\/i><\/li>\n
    4. Look for the line that starts with\u00a0BatchPresortCacheSize =<\/em><\/i><\/li>\n
    5. If the value does not exist, create one and assign the first locator input field to sort by.\u00a0 Repeat the entry for additional fields
      \nBatchPresortCacheSize = 100000<\/em><\/i><\/li>\n
    6. Save the locator.<\/li>\n
    7. Use the locator and compare performance and system memory use.<\/li>\n<\/ol>\n

      In this example I geocoded 10,000 unsorted U.S. addresses with a U.S. streets locator and the preceding enhancements.\u00a0 Performance increased from 350,000 recs\/hr to 614,000 recs\/hr.\u00a0 You can experiment with the\u00a0 batch presort cache size to find optimal performance for your locators and data.<\/p>\n

      In the future we\u2019ll look at more ways to increase geocoding performance, but these techniques are a good start and should result in some excellent results.<\/p>\n

      Jeff<\/p>\n"}],"authors":[{"ID":3961,"user_firstname":"Jeff","user_lastname":"Rogers","nickname":"Jeff Rogers","user_nicename":"jrogers","display_name":"Jeff Rogers","user_email":"jrogers@esri.com","user_url":"","user_registered":"2018-03-02 00:15:36","user_description":"Jeff Rogers is the Product Development Director for Geocoding at Esri. For nearly 20 years Jeff has worked on supporting the ArcGIS platform with comprehensive geocoding capabilities. Jeff has also lead ArcGIS data projects such as ArcGIS Data and Maps and StreetMap Premium as well as route planning and navigation solutions.","user_avatar":""}],"related_articles":"","card_image":false,"wide_image":false},"yoast_head":"\nImproving batch geocoding performance<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-desktop\/analytics\/improving-batch-geocoding-performance\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Improving batch geocoding performance\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.esri.com\/arcgis-blog\/products\/arcgis-desktop\/analytics\/improving-batch-geocoding-performance\" \/>\n<meta property=\"og:site_name\" content=\"ArcGIS Blog\" \/>\n<meta property=\"article:publisher\" 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