DEMONSTRATION (Video)

Web Poral

Login

1. We prepare a test account for the reviewers. UserName: JustTestUser, Password:JustTestUser!1
2. Enter the login page: http://portal-just.urban-computing.cn/login
3. Enter the User Name (JustTestUser) and Password (JustTestUser!1), then click the button Login, as shown in the following picture.

Figure 1: Login.

Web Poral

As shown in Figure 2, the web portal of JUST-Traj has three panels: (1) table panel, which manages the created tables; (2) SQL panel, which provides an SQL editor; and (3) result panel, which visualizes the result by multiple display forms, i.e., table view, chart view (i.e., histogram and line chart), and map view.

Figure 2: Web portal.

Create Table

JUST-Traj uses the following statement to create a trajectory table: CREATE TABLE <table name> (<field name > Trajectory), where field name is the field name of the trajectory in the database. For example,

CREATE TABLE traj_table (traj Trajectory)

Load Data

We can load data from multiple sources into JUST-Traj using the following statement: LOAD <source type>:<file path> TO JUST:<table name> CONFIG {<the field mapping relationship>}; where source type could be HDFS, HIVE, KAFAK, FLINK, and the CONFIG provides the field mapping between the source and the JUST-Traj table.

For example, we load data from HDFS to JUST-Traj.

x
LOAD HDFS:'/just_tutorial/trajectory_data' to JUST:traj_table ( 
traj.oid 0, 
traj.time to_timestamp(3), 
traj.point st_makePoint(1,2) 
);         

where `/trajectories' is the path of trajectories, lines from 2 to 4 are the field mappings.

Query

JUST-Traj provides spatial or spatio-temporal queries: e.g., spatial range query, spatio-temporal range query, ID temporal query, kNN query.

(1) Spatial query: SELECT * FROM traj_table WHERE (traj, st_makeBBox(lng1,lat1, lng2, lat2); where, spatial relationship could be $st\mathrm{\_}within$$st\_within$, $st\mathrm{\_}intersect$$st\_intersect$, $st\mathrm{\_}overlap$$st\_overlap$. st_makeBBox is a spatial range formed by two points ($lng1,lat1$$lng1,lat1$) and ($lng2,lat2$$lng2, lat2$).

For example,

x
select
    traj_linestring(traj) geom
from
    traj_table
where
    st_within(traj_linestring(traj), st_makeBBox(113.0, 23.0, 113.5, 23.6));

(2) Spatio-temporal query

x
SELECT * FROM traj_table
WHERE st_within(traj_linestring(traj), st_makeBBox(113.0, 23.0, 113.5, 23.6))
  and traj_startTime(traj) >= '2014-03-13 07:04:51'
  and traj_endTime(traj) <= '2014-03-16 08:04:51';

(3) ID-temporal query

x
SELECT * FROM traj_table
WHERE 
  traj_oid(traj) = '1003'
  and traj_startTime(traj) >= '2013-07-03 14:33:27'
  and traj_endTime(traj) <= '2018-08-03 14:33:27'

(4) Similarity Query

x
select
  *
from
  traj_table
where
  st_distanceWithin(
    traj,
    'LINESTRING (111.64161523718602 22.632099487568006,111.64196120470221 22.635834170510613,
      111.7091216719027 22.589810068829873)',
    'frechet',
    20000.0
  )

(5) K-NN query

x
SELECT
  *
FROM
  traj_table
WHERE
  st_knn(
    traj,
    'POINT(115.71 39.57)',
    'common',
    10
  )

Analytics

JUST-Traj supports many out-of-the-box analyses on trajectories, which facilitates the development of applications. The SQL statement of DAL is as follows: SELECT <analysis operation>(traj, {<parameters>}) FROM <table name>; where, analysis operation is the name of analysis on trajectories, parameters set the corresponding parameters. Five common analyses provided by JUST-Traj, i.e.,

Processing. Although we can pre-process before storing, the parameter of each algorithm could be adjusted when analyzing. Thus, JUST-Traj also supports the processing in the analytics stage;

(1) Noise Filtering

x
SELECT
  st_trajnoisefilter(
     traj,
    '{ "filterType": "COMPLEX_FILTER",
      "maxSpeedMeterPerSecond": 100.0,
      "segmenterParams": { "maxTimeIntervalInMinute": 60,
      "maxStayDistInMeter": 100,
      "minStayTimeInSecond": 100,
      "minTrajLengthInKM": 1,
      "segmenterType": "ST_DENSITY_SEGMENTER"}}'
  )
FROM
  traj_table
LIMIT 1000

(2) Segmentation

x
SELECT st_trajSegmentation(traj,
    '{ "maxTimeIntervalInMinute": 10,
      "maxStayDistInMeter": 100,
      "minStayTimeInSecond": 100,
      "minTrajLengthInKM": 1,
      "segmenterType": "HYBRID_SEGMENTER"
    }'
  )
FROM traj_table
LIMIT 1000

(3) Interpolation

x
SELECT st_freespaceInterpolation(
    traj, 30)
FROM traj_table
LIMIT 100

(4) MapMatching

create a trajectory table for MapMatching

x
CREATE TABLE mm_traj (traj Trajectory)

Load Data

x
LOAD hdfs: '/just_ci_data/mm_traj.csv' to just: mm_traj(
 traj traj_recover(traj)
)WITH (
"just.separator"="|",
"just.header"="true"
)

create a road network table

x
create table if not exists longgang_expand_rn (
  road RoadSegment,
  weight Double
);

Load Data

LOAD hdfs: '/just_ci_data/longgang_expand_rn.csv' to just: longgang_expand_rn (
          road.oid oid,
          road.geom st_lineFromText(geom),
          road.direction direction,
          road.level level,
          road.speed_limit speed_limit,
          weight weight
) WITH (
"just.separator"="|",
"just.header"="true"
)

MapMatching

ST_trajMapMatchToProjection

x
select 
 ST_trajMapMatchToProjection(
 t1.traj,t2.t
 )
from
 mm_traj t1,
 (select ST_makeRoadNetwork(collect_list(road))as t FROM longgang_expand_rn) as t2

ST_trajMapMatchToRoute

x
SELECT
  st_trajMapMatchToRoute(
    t1.traj,
    t2.t
  )
FROM
  mm_traj t1,
 (SELECT st_makeRoadNetwork(collect_list(road))as t FROM longgang_expand_rn) AS t2

Aggregation. JUST-Traj provides many aggregation operations, e.g., $max()$$max()$, $min()$$min()$, $count()$$count()$; For example,

x
SELECT count(*) FROM traj_table;

Stay Point Detection. Moving objects tend to stay due to certain events, such as vehicles staying for refueling, couriers staying for delivery. By analyzing the place that a mobile object stays, we can infer to some places of interesting, e.g., the delivery address;

x
SELECT st_trajStayPoint(traj,
  '{ "maxStayDistInMeter": 10,
     "minStayTimeInSecond": 60}')
FROM
  traj_table
LIMIT 1000

Holistic Solutions

Spatio-temporal Query and Stay Point Detection In this scenario, we detect stay points from the spatio-temporal query result. We define the location where the lorry stays over a given time threshold (minStayTimeInSecond) as a stay point, where the location is a spatial region whose maximum distance not greater than a distance threshold (maxStayDisInMeter). The underlying locations of stay points could be the delivery addresses. The SQL is as follows:

x
SELECT st_trajStayPoint(traj,
  '{ "maxStayDistInMeter": 10,
     "minStayTimeInSecond": 60}')
FROM
  traj_table
WHERE
  st_within(traj_linestring(traj), 
      st_makeBBox(113.0, 23.0, 113.5, 23.6))
  and traj_startTime(traj) >= '2014-03-13 07:04:51'
  and traj_endTime(traj) <= '2014-03-16 08:04:51'

Lines from 7 to 10 take a spatio-temporal range to query trajectories from the database. Lines from 1 to 3 execute the Stay Point Detection operation on the extracted trajectories, where lines from 2 to 3 are parameters of Stay Point Detection.

ID Temporal Query and Noise Filtering

In this scenario, we define the point whose speed exceeds the maximum limited speed (maxSpeedMeterPerSecond) as the noise point, and we filter that point. The SQL is as follows:

LOADING trajectories of Guiyang:

x
LOAD HDFS :'/just_tutorial/guiyang_traj' to JUST :traj_table (
  traj.oid 1,
  traj.time to_timestamp(0),
  traj.point st_makePoint(3, 2)
)

The raw trajectory

x
SELECT
  traj_linestring(traj)
FROM
  traj_table
WHERE
  traj_oid(traj) = '1192408782';

Noise Filtering

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SELECT
  traj_linestring(aa.item)
from
  (
    SELECT
      st_trajnoisefilter(
        traj,
        '{ "filterType": "COMPLEX_FILTER",
      "maxSpeedMeterPerSecond": 20.0,
      "segmenterParams": { "maxTimeIntervalInMinute": 10,
      "maxStayDistInMeter": 100,
      "minStayTimeInSecond": 100,
      "minTrajLengthInKM": 1,
      "segmenterType": "ST_DENSITY_SEGMENTER"}}'
      )
    FROM
      traj_table
    WHERE
      traj_oid(traj) = '1192408782'
  and traj_startTime(traj) >= '2018-06-03 14:33:27'
  and traj_endTime(traj) <= '2018-08-03 14:33:27'
  ) as aa

Lines from 7 to 9 take a ID Temporal query to extract trajectories from the database. Lines from 1 to 3 execute the Noise Filtering operation on the extracted trajectories.

Download Back Results

xxxxxxxxxx
DOWNLOAD
SELECT
  st_trajStayPoint(
    traj,
    '{ "maxStayDistInMeter": 10,      "minStayTimeInSecond": 60}'
  )
FROM
  traj_table
WHERE
  st_within(
    traj_linestring(traj),
    st_makeBBox(113.0, 23.0, 113.5, 23.6)
  )
  and traj_startTime(traj) >= '2014-03-13 07:04:51'
  and traj_endTime(traj) <= '2014-03-16 08:04:51'

Results

DB-Driver

Download DB-Driver

The DB Driver is a Java-based API for accessing JUST-Traj DB. It complies with the JDBC specification, implements most of the interfaces, and extends some space-time attributes. Users can download the just-drive-java.jar from http://nexus.cbpmgt.com/nexus/#nexus-search;quick~just-driver-java.

Quick Start

Because the API follow the JDBC specification, so we can according to the JDBC API to access DB. The official document of JDBC: https://docs.oracle.com/javase/tutorial/jdbc/basics/index.html.

Parameters

• The first is the JDBC URL. JUST begins with JDBC: JUST: followed by a parameter in the form key=value;

• Note: Urls must be configured = XXX;

• There are three ways to pass a parameter. For example, access to JUST requires user key authentication:

  • Specify the username secret key in the URL: jdbc:just:urls=https://portal-just.urban-computing.cn/server2;user=xxx;privateKey=xxx;

  • Specify by code;

    xxxxxxxxxx
    Use native Properties to set parameters: JustProperties essentially just inherits Properties and extends a few methods. When using Properties, users need to pay attention to whether the key of these parameters changes, so it is not recommended
    

  • Use native Properties to set parameters: JustProperties essentially just inherits Properties and extends a few methods. When using Properties, users need to pay attention to whether the key of these parameters changes, so it is not recommended.

Demo

Here's a demo to use DB-Driver

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final JustProperties p = new JustProperties("xxx", "sec");
p.setDB("my_db");
p.setPageSize(1000);
try (final Connection connection = DriverManager.getConnection("jdbc:just:urls=http://xxxx", p)) {
    final Statement statement = connection.createStatement();
    final ResultSet rs = statement.executeQuery("select attr1,attr2,attr3 as a3 from order_table");
    final ResultSetMetaData md = rs.getMetaData();
    final int columnCount = md.getColumnCount();
    assertEquals(3, columnCount);
    while (rs.next()) {
        assertNotNull(rs.getString(1));
        assertNotNull(rs.getString(2));
        assertNotNull(rs.getString(3));
        assertNotNull(rs.getString("attr1"));
        assertNotNull(rs.getString("attr2"));
        assertNotNull(rs.getString("a3"));
    }
}

For trajectory

Create table

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String sql  = "CREATE TABLE traj_table (traj Trajectory)";
Statement stmt = connection.createStatement();
stmt.executeUpdate(sql);

Load Data

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String sql  = "LOAD HDFS:'/just_tutorial/trajectory_data' to JUST:traj_table (trajectory.oid 0,    trajectory.time to_timestamp(3),    trajectory.point st_makePoint(1,2)); ";
Statement stmt = connection.createStatement();
stmt.executeUpdate(sql);

Query

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String sql = "sql";
final Statement st = connection.createStatement();
final JustResultSet rs = (JustResultSet) st.executeQuery(sql);

where "sql" is the query statement provided by JUST-Traj. e.g., for spatial query

xxxxxxxxxx
String sql = "select traj_linestring(traj) geom from traj_table where    st_within(traj_linestring(traj), st_makeBBox(113.0, 23.0, 113.5, 23.6))";
final Statement st = connection.createStatement();
final JustResultSet rs = (JustResultSet) st.executeQuery(sql);
while (rs.hasNext()) {
    System.out.println(rs.next().getString(1));
}

other queries can refer to the statements described in Web portal.