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This chapter is from the book

Case Study: Customer Manifests

Chapter 1, “Different Databases for Different Requirements,” introduced TransGlobal Transport and Shipping (TGTS), a fictitious transportation company that coordinates the movement of goods around the globe for businesses of all sizes. As business has grown, TGTS is transporting and tracking more complicated and varied shipments. Analysts have gathered requirements and some basic estimates about the number of containers that will be shipped. They found a mix of common fields for all containers and specialized fields for different types of containers.

All containers will require a core set of fields such as customer name, origination facility, destination facility, summary of contents, number of items in container, a hazardous material indicator, an expiration date for perishable items such as fruit, a destination facility, and a delivery point of contact and contact information.

In addition, some containers will require specialized information. Hazardous materials must be accompanied by a material safety data sheet (MSDS), which includes information for emergency responders who may have to handle the hazardous materials. Perishable foods must also have details about food inspections, such as the name of the person who performed the inspection, the agency responsible for the inspection, and contact information of the agency.

The analyst found that 70%–80% of the queries would return a single manifest record. These are typically searched for by a manifest identifier or by customer name, date of shipment, and originating facility. The remaining 20%–30% would be mostly summary reports by customers showing a subset of common information. Occasionally, managers will run summary reports by type of shipment (for example, hazardous materials, perishable foods), but this is rarely needed.

Executives inform the analysts that the company has plans to substantially grow the business in the next 12 to 18 months. The analysts realize that they may have many different types of cargo in the future with specialized information, just as hazardous materials and perishable foods have specialized fields. They also realize they must plan for future scaling up and the need to support new fields in the database. They concluded that a document database that supports horizontal scaling and a flexible schema is required.

The analysts start the document and collection design process by considering fields that are common to most manifests. They decided on a collection called Manifests with the following fields:

  • Customer name
  • Customer contact person’s name
  • Customer address
  • Customer phone number
  • Customer fax
  • Customer email
  • Origination facility
  • Destination facility
  • Shipping date
  • Expected delivery date
  • Number of items in container

They also determine fields they should track for perishable foods and hazardous materials. They decide that both sets of specialized fields should be grouped into their own documents. The next question they have to decide is, should those documents be embedded with manifest documents or should they be in a separate collection?

Embed or Not Embed?

The analysts review sample reports that managers have asked for and realize that the perishable foods fields are routinely reported along with the common fields in the manifest. They decide to embed the perishable foods within the manifest document.

They review sample reports and find no reference to the MSDS for hazardous materials. They ask a number of managers and executives about this apparent oversight. They are eventually directed to a compliance officer. She explains that the MSDS is required for all hazardous materials shipments. The company must demonstrate to regulators that their database includes MSDSs and must make the information available in the event of an emergency. The compliance officer and analyst conclude they need to define an additional report for facility managers who will run the report and print MSDS information in the event of an emergency.

Because the MSDS information is infrequently used, they decide to store it in a separate collection. The Manifest collection will include a field called msdsID that will reference the corresponding MSDS document. This approach has the added benefit that the compliance officer can easily run a report listing any hazardous material shipments that do not have an msdsID. This allows her to catch any missing MSDSs and continue to comply with regulations.

Choosing Indexes

The analysts anticipate a mix of read and write operations with approximately 60%–65% reads and 35%–40% writes. They would like to maximize the speed of both reads and writes, so they carefully weigh the set of indexes to create.

Because most of the reads will be looks for single manifests, they decide to focus on that report first. The manifest identifier is a logical choice for index field because it is used to retrieve manifest doccuments.

Analysts can also look up manifests by customer name, shipment date, and origination facility. The analysts consider creating three indexes: one for each field. They realize, however, that they will rarely need to list all shipments by date or by origination facility, so they decide against separate indexes for those fields.

Instead, they create a single index on all three fields: customer name, shipment date, and origination facility. With this index, the database can determine if a manifest exists for a particular customer, shipping date, and origination facility by checking the index only; there is no need to check the actual collection of documents, thus reducing the number of read operations that have to be performed.

Separate Collections by Type?

The analysts realize that they are working with a small number of manifest types, but there may be many more in the future. For example, the company does not ship frozen goods now, but there has been discussion about providing that service. The analysts know that if you frequently filter documents by type, it can be an indicator that they should use separate collections for each type.

They soon realize they are the exception to that rule because they do not know all the types they may have. The number of types can grow quite large, and managing a large number of collections is less preferable to managing types within a single collection.

By using requirements for reports and keeping in mind some basic design principles, the analysts are able to quickly create an initial schema for tracking a complex set of shipment manifests.

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