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Datasets

chengsijin0817 edited this page Jan 28, 2019 · 24 revisions

This document describes the dataset that is used for the Linköping GraphQL Benchmark (LinGBM). The dataset of LinGBM is generated by the BSBM data generator, which is based on an e-commerce use case. The dataset contains 9 entities and 8 relationships. Producers produce a set of products, which is offered by different vendors and different consumers have posted reviews about products.

Relational model

This part shows the relational model of the dataset. The BSBM data generator could output the dataset as a MySQL dump. This dump uses the following entity relationship and relational schema:

The detailed information of cardinalities of the relationships refers to:

Relationship

Relationship cardinalities note
Producer-Product 1: N One producer per Product; 50 products on average per producer
Product-Review 1: N 10 reviews per product on average; 1 product per Review, selection follows a normal distribution
Product-Offer 1: N 20 Offers on average per product; one Product per offer, selection follows a normal distribution
Person- Review 1: N one author per Review; 20 reviews per person on average
Ratingsite-Review 1: N Every Review belongs to one rating site; A rating site generated 10000 reviews on average
Vendors-Offers 1: N one offer belongs to a vendor; 2000 offers on average per vendor
Product-ProductType N:1 1 ProductType per product (leaves only)
Product-ProductFeature M: N 10-20 ProductFeatures per product

Relational schema:

Vendor (nr, label, comment, homepage, country)
Offer (nr, product, producer, vendor, price, validFrom, validTo, deliveryDays, offerWebpage)
Producer (nr, label, comment, homepage, country)
Product (nr, label, comment, producer, propertyNum1, propertyNum2, propertyNum3, propertyNum4, propertyNum5, propertyNum6, propertyTex1, propertyTex2, propertyTex3, propertyTex4, propertyTex5, propertyTex6)
Person (nr, name, mbox_sha1sum, country)
Review (nr, product, producer, person, reviewDate, title, text, language, rating1, rating2, rating3, rating4, publisher)
ProductFeature (nr, label, comment)
ProductType (nr, label, comment, parent)
ProductTypeProduct (product, productType)
ProductFeatureProduct (product, productFeature)

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