Shulou(Shulou.com)06/01 Report--

In this issue, Xiaobian will bring you about TableStore how to easily implement track management and geofencing. The article is rich in content and analyzed and described from a professional perspective. After reading this article, I hope you can gain something.

I. Programme background

Trajectory management systems are commonly used in daily life, such as take-out delivery trajectories, express logistics circulation, vehicle positioning trajectories, etc. This scenario is similar to geographical location management, with the core point and bottleneck both in the storage performance and query capability of the database, and at the same time, the time field needs to be arranged in positive order to ensure the order of track points; on the one hand, the storage service needs to cope with the low latency storage and reading of massive data, on the other hand, the storage service also needs to provide efficient multi-dimensional data retrieval and sorting. TableStore is still competent for trajectory management scenarios and fully capable of implementing trajectory management systems.

Let's experience the example of [100 million motorcycle management system] built based on TableStore;

demand scenarios

For safety reasons, motorcycles are restricted from entering certain areas in the urban area of a city. A motorcycle rental company, in order to better manage the motorcycle violations under its jurisdiction, installed a positioning system on its own motorcycle to collect the motorcycle position regularly. Motorcycle rental companies can query and count violations through the track management platform, and can also be used as a basis to remind illegal rental users that excessive violations are blacklisted;

Query scenario: motorcycle driving track and violation query with No.[id00001] on November 1, 2018;

An example is as follows:

Note: This example provides [100 million magnitude] trajectory data. Official website console address: Project sample

cdn.com/d61994c78686ae667deffa8a58bf9f0777f8faac.gif">

The sample is embedded in the table storage console, and users can log in to the console experience system (if it is a new user of table storage, you need to click to open the service to experience, and the opening is free. The order data is stored in the public instance, and the experience does not consume user storage, traffic, and Cu).

TableStore scheme

Using TableStore to easily build a set of: 100 million motorcycle management system. Multi-index function provides GEO retrieval, multi-dimensional query ability, through the sorting of time to obtain the track of tracking equipment. At the same time, users can create indexes at any time and then complete automatic synchronization without worrying about inventory data problems.

TableStore, as a fully hosted, zero-O distributed NoSql data storage service provided by Alibaba Cloud, has functions such as mass data storage, automatic fragmentation of hot data, and multidimensional retrieval of mass data, effectively solving the challenge of large expansion of GEO data volume;

SearchIndex function provides the ability of multi-dimensional data search and sorting on the basis of ensuring the high availability of user data. Create multiple indexes for multiple scenarios to achieve multiple mode retrieval. Users can create and open indexes only when needed. TableStore ensures the consistency of data synchronization, which greatly reduces the workload of user solution design, service operation and maintenance, code development, etc.

II. Preparation for construction

If you have a good experience with TableStore-based [Billion Scale Motorcycle Management System] and want to start your own system construction journey, just follow the following steps to start building:

1. Open table storage

The form storage service is opened through the console, and the form storage is ready to use (post-payment). The pay-per-use method has been adopted, and the user has been provided with sufficient free quota for functional testing. The table stores the official website console, free quota description.

2. Create an instance

Create a tabular storage instance from the console and select a Region that supports multivariate indexing. (SearchIndex function has not been commercialized at the current stage, temporarily open Beijing, Shanghai, Hangzhou and Shenzhen, the rest of the region will gradually open)

After the instance is created, submit a ticket to apply for multi-index function invitation test (it is enabled by default after commercialization, and there is no charge if it is not used).

Test invitation address: submit a work order, select Table Storage> Product Function and Feature Consultation> Create Work Order, and the application contents are as follows:

Question Description: Please fill in [Request SearchIndex]

Confidential information: Please fill in [Region + Instance Name], e.g. Shanghai +myInstanceName

3, SDK download

Using SDK with multiple index (SearchIndex), official website address, temporarily java, go, node.js three SDK added new features

java-SDK com.aliyun.openservices tablestore 4.7.4go-SDK$ go get github.com/aliyun/aliyun-tablestore-go-sdk4, Table Design

Store search system sample, simple use of only a store table, mainly contains fields: store type, store name, store location, store average score, per capita consumption, etc. The table is designed as follows:

Name: geo_track

Column Name Data Type Index Type Field Description_id(Primary Key Column)String

MD5(mId + timestamp) Avoid hot spots mIdStirng

Motorcycle No. timestamplongLONG time point (millisecond timestamp) posStringGEO_POINT Vehicle position: "30.132,120.082"(latitude, precision)..................................... 3. Start building (core code) 1. Create a data table

Users only need to create "motorcycle track table" under the instance that completes the test invitation: create and manage the data table through the console (users can also create it directly through SDK): other tables, such as rental user table, motorcycle information table, etc., are created according to requirements: only track table is displayed here, table name: geo_track

2. Create a data table index

TableStore automates full, incremental index data synchronization: users can create and manage indexes through the console (or create indexes through the SDK)

3. Data import

Insert some test data (108 million pieces (70 days) of data are inserted into the console sample, and users can insert a small amount of test data through the console themselves);

Name: geo_track

Motorcycle number track point md5(mId + timestamp)(primary key) time shop location id00001f50d55bec347253c24dc9144dff3e3b715411036000030.30094,120.01278

TableName: moto_user

Motorcycle number (primary key) Motorcycle color Motorcycle brand Motorcycle rental user id00001 Silver gray H brand Motorcycle Yang Liu 4. Data reading

Data reading falls into two categories:

Primary key reading (motorcycle information query)

Get primary key columns based on native table storage: getRow, getRange, batchGetRow, etc. Primary key reading is used for index (automatic) reverse query, users can also provide primary key (motorcycle number) single query page, query speed is very fast. Multi-dimensional retrieval is not supported for single primary key query.

Index reading (track information query)

Based on the new SearchIndex feature Query: search interface. Users can freely design multi-dimensional condition combination queries for index fields. By setting and selecting different query parameters, different query conditions and different sorting methods are constructed. Currently, precise query, range query, prefix query, matching query, wildcard query, phrase matching query, word string query are supported, and Boolean and, or combination is adopted.

For example,[November 01, 2018, id00001 motorcycle, driving track and violation inquiry] Query conditions are as follows:

List mustQueries = new ArrayList();List polygonList = Arrays.asList(//geofence, forbidden area "30.262348,120.092127", "30.311668,120.079761", "30.332413,120.129371", ...); String mId = "id00001";Long timeStart = [2018-11-01 timestamp];Long timeEnd = [2018-11-02 timestamp];GeoPolygonQuery geoPolygonQuery = new GeoPolygonQuery();geoPolygonQuery.setPoints (polygonList);geoPolygonQuery.setFieldName("pos");mustQueries.add (geoPolygonQuery);TermQuery termQuery = new TermQuery();termQuery.setFieldName("mId");termQuery.setTerm (ColumnValue.fromString(request.getmId()));mustQueries.add (termQuery);RangeQuery rangeQuery = new RangeQuery();rangeQuery.setFieldName ("timestamp");rangeQuery.setFrom (ColumnValue.fromDouble(timeStart, true);rangeQuery.setTo (ColumnValue.fromDouble(timeEnd, false);mustQueries.add (rangeQuery);BoolQuery boolQuery = new BoolQuery();boolQuery.setMustQueries (mustQueries); The above is how TableStore, which is shared by everyone, can easily implement track management and geofencing. If there are similar doubts, please refer to the above analysis for understanding. If you want to know more about it, please pay attention to the industry information channel.

Welcome to subscribe "Shulou Technology Information " to get latest news, interesting things and hot topics in the IT industry, and controls the hottest and latest Internet news, technology news and IT industry trends.