MatchGraphRequest (Kinetica Java API 7.0.19.0 API)

java.lang.Object
- com.gpudb.protocol.MatchGraphRequest

All Implemented Interfaces:

org.apache.avro.generic.GenericContainer, org.apache.avro.generic.IndexedRecord
```
public class MatchGraphRequest
extends Object
implements org.apache.avro.generic.IndexedRecord
```
A set of parameters for GPUdb.matchGraph(MatchGraphRequest).
Matches a directed route implied by a given set of latitude/longitude points to an existing underlying road network graph using a given solution type. IMPORTANT: It's highly recommended that you review the Network Graphs & Solvers concepts documentation, the Graph REST Tutorial, and/or some /match/graph examples before using this endpoint.

Nested Class Summary

Nested Classes
Modifier and Type	Class and Description
`static class`	`MatchGraphRequest.Options` Additional parameters `GPS_NOISE`: GPS noise value (in meters) to remove redundant sample points.
`static class`	`MatchGraphRequest.SolveMethod` The type of solver to use for graph matching.

Constructor Summary

Constructors
Constructor and Description
`MatchGraphRequest()` Constructs a MatchGraphRequest object with default parameters.
`MatchGraphRequest(String graphName, List<String> samplePoints, String solveMethod, String solutionTable, Map<String,String> options)` Constructs a MatchGraphRequest object with the specified parameters.

Method Summary

All Methods Static Methods Instance Methods Concrete Methods
Modifier and Type	Method and Description
`boolean`	`equals(Object obj)`
`Object`	`get(int index)` This method supports the Avro framework and is not intended to be called directly by the user.
`static org.apache.avro.Schema`	`getClassSchema()` This method supports the Avro framework and is not intended to be called directly by the user.
`String`	`getGraphName()`
`Map<String,String>`	`getOptions()`
`List<String>`	`getSamplePoints()`
`org.apache.avro.Schema`	`getSchema()` This method supports the Avro framework and is not intended to be called directly by the user.
`String`	`getSolutionTable()`
`String`	`getSolveMethod()`
`int`	`hashCode()`
`void`	`put(int index, Object value)` This method supports the Avro framework and is not intended to be called directly by the user.
`MatchGraphRequest`	`setGraphName(String graphName)`
`MatchGraphRequest`	`setOptions(Map<String,String> options)`
`MatchGraphRequest`	`setSamplePoints(List<String> samplePoints)`
`MatchGraphRequest`	`setSolutionTable(String solutionTable)`
`MatchGraphRequest`	`setSolveMethod(String solveMethod)`
`String`	`toString()`

Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait

- Constructor Detail
  - MatchGraphRequest
```
public MatchGraphRequest()
```
    Constructs a MatchGraphRequest object with default parameters.
  - MatchGraphRequest
```
public MatchGraphRequest(String graphName,
                         List<String> samplePoints,
                         String solveMethod,
                         String solutionTable,
                         Map<String,String> options)
```
    Constructs a MatchGraphRequest object with the specified parameters.
    Parameters:
    
    graphName - Name of the underlying geospatial graph resource to match to using samplePoints.
    
    samplePoints - Sample points used to match to an underlying geospatial graph. Sample points must be specified using identifiers; identifiers are grouped as combinations. Identifiers can be used with: existing column names, e.g., 'table.column AS SAMPLE_X'; expressions, e.g., 'ST_MAKEPOINT(table.x, table.y) AS SAMPLE_WKTPOINT'; or constant values, e.g., '{1, 2, 10} AS SAMPLE_TRIPID'.
    solveMethod - The type of solver to use for graph matching. Supported values:
    
    MARKOV_CHAIN: Matches samplePoints to the graph using the Hidden Markov Model (HMM)-based method, which conducts a range-tree closest-edge search to find the best combinations of possible road segments (num_segments) for each sample point to create the best route. The route is secured one point at a time while looking ahead chain_width number of points, so the prediction is corrected after each point. This solution type is the most accurate but also the most computationally intensive. Related options: num_segments and chain_width.
    MATCH_OD_PAIRS: Matches samplePoints to find the most probable path between origin and destination pairs with cost constraints.
    MATCH_SUPPLY_DEMAND: Matches samplePoints to optimize scheduling multiple supplies (trucks) with varying sizes to varying demand sites with varying capacities per depot. Related options: partial_loading and max_combinations.
    MATCH_BATCH_SOLVES: Matches samplePoints source and destination pairs for the shortest path solves in batch mode.
    The default value is MARKOV_CHAIN.
    solutionTable - The name of the table used to store the results; this table contains a track of geospatial points for the matched portion of the graph, a track ID, and a score value. Also outputs a details table containing a trip ID (that matches the track ID), the latitude/longitude pair, the timestamp the point was recorded at, and an edge ID corresponding to the matched road segment. Has the same naming restrictions as tables. Must not be an existing table of the same name. The default value is ''.
    options - Additional parameters
    
    GPS_NOISE: GPS noise value (in meters) to remove redundant sample points. Use -1 to disable noise reduction. The default value accounts for 95% of point variation (+ or -5 meters). The default value is '5.0'.
    NUM_SEGMENTS: Maximum number of potentially matching road segments for each sample point. For the markov_chain solver, the default is 3. The default value is '3'.
    SEARCH_RADIUS: Maximum search radius used when snapping sample points onto potentially matching surrounding segments. The default value corresponds to approximately 100 meters. The default value is '0.001'.
    CHAIN_WIDTH: For the markov_chain solver only. Length of the sample points lookahead window within the Markov kernel; the larger the number, the more accurate the solution. The default value is '9'.
    SOURCE: Optional WKT starting point from samplePoints for the solver. The default behavior for the endpoint is to use time to determine the starting point. The default value is 'POINT NULL'.
    DESTINATION: Optional WKT ending point from samplePoints for the solver. The default behavior for the endpoint is to use time to determine the destination point. The default value is 'POINT NULL'.
    PARTIAL_LOADING: For the match_supply_demand solver only. When false (non-default), trucks do not off-load at the demand (store) side if the remainder is less than the store's need Supported values:
    
    TRUE: Partial off-loading at multiple store (demand) locations
    FALSE: No partial off-loading allowed if supply is less than the store's demand.
    The default value is TRUE.
    MAX_COMBINATIONS: For the match_supply_demand solver only. This is the cutoff for the number of generated combinations for sequencing the demand locations - can increase this up to 2M. The default value is '10000'.
    LEFT_TURN_PENALTY: This will add an additonal weight over the edges labelled as 'left turn' if the 'add_turn' option parameter of the GPUdb.createGraph(CreateGraphRequest) was invoked at graph creation. The default value is '0.0'.
    RIGHT_TURN_PENALTY: This will add an additonal weight over the edges labelled as' right turn' if the 'add_turn' option parameter of the GPUdb.createGraph(CreateGraphRequest) was invoked at graph creation. The default value is '0.0'.
    INTERSECTION_PENALTY: This will add an additonal weight over the edges labelled as 'intersection' if the 'add_turn' option parameter of the GPUdb.createGraph(CreateGraphRequest) was invoked at graph creation. The default value is '0.0'.
    SHARP_TURN_PENALTY: This will add an additonal weight over the edges labelled as 'sharp turn' or 'u-turn' if the 'add_turn' option parameter of the GPUdb.createGraph(CreateGraphRequest) was invoked at graph creation. The default value is '0.0'.
    AGGREGATED_OUTPUT: For the match_supply_demand solver only. When it is true (default), each record in the output table shows a particular truck's scheduled cumulative round trip path (MULTILINESTRING) and the corresponding aggregated cost. Otherwise, each record shows a single scheduled truck route (LINESTRING) towards a particular demand location (store id) with its corresponding cost. The default value is 'true'.
    MAX_TRIP_COST: For the match_supply_demand solver only. If this constraint is greater than zero (default) then the trucks will skip travelling from one demand location to another if the cost between them is greater than this number (distance or time). Zero (default) value means no check is performed. The default value is '0.0'.
    FILTER_FOLDING_PATHS: For the markov_chain solver only. When true (non-default), the paths per sequence combination is checked for folding over patterns and can significantly increase the execution time depending on the chain width and the number of gps samples. Supported values:
    
    TRUE: Filter out the folded paths.
    FALSE: Do not filter out the folded paths
    The default value is FALSE.
    UNIT_UNLOADING_COST: For the match_supply_demand solver only. The unit cost per load amount to be delivered. If this value is greater than zero (default) then the additional cost of this unit load multiplied by the total dropped load will be added over to the trip cost to the demand location. The default value is '0.0'.
    MAX_NUM_THREADS: For the markov_chain solver only. If specified (greater than zero), the maximum number of threads will not be greater than the specified value. It can be lower due to the memory and the number cores available. Default value of zero allows the algorithm to set the maximal number of threads within these constraints. The default value is '0'.
    TRUCK_SERVICE_LIMIT: For the match_supply_demand solver only. If specified (greather than zero), any truck's total service cost (distance or time) will be limited by the specified value including multiple rounds (if set). The default value is '0.0'.
    ENABLE_TRUCK_REUSE: For the match_supply_demand solver only. If specified (true), all trucks can be scheduled for second rounds from their originating depots. Supported values:
    
    TRUE: Allows reusing trucks for scheduling again.
    FALSE: Trucks are scheduled only once from their depots.
    The default value is FALSE.
    The default value is an empty Map.
- Method Detail
  - getClassSchema
```
public static org.apache.avro.Schema getClassSchema()
```
    This method supports the Avro framework and is not intended to be called directly by the user.
    
    Returns:
    
    the schema for the class.
  - getGraphName
```
public String getGraphName()
```
    Returns:
    
    Name of the underlying geospatial graph resource to match to using samplePoints.
  - setGraphName
```
public MatchGraphRequest setGraphName(String graphName)
```
    Parameters:
    
    graphName - Name of the underlying geospatial graph resource to match to using samplePoints.
    
    Returns:
    
    this to mimic the builder pattern.
  - getSamplePoints
```
public List<String> getSamplePoints()
```
    Returns:
    
    Sample points used to match to an underlying geospatial graph. Sample points must be specified using identifiers; identifiers are grouped as combinations. Identifiers can be used with: existing column names, e.g., 'table.column AS SAMPLE_X'; expressions, e.g., 'ST_MAKEPOINT(table.x, table.y) AS SAMPLE_WKTPOINT'; or constant values, e.g., '{1, 2, 10} AS SAMPLE_TRIPID'.
  - setSamplePoints
```
public MatchGraphRequest setSamplePoints(List<String> samplePoints)
```
    Parameters:
    
    samplePoints - Sample points used to match to an underlying geospatial graph. Sample points must be specified using identifiers; identifiers are grouped as combinations. Identifiers can be used with: existing column names, e.g., 'table.column AS SAMPLE_X'; expressions, e.g., 'ST_MAKEPOINT(table.x, table.y) AS SAMPLE_WKTPOINT'; or constant values, e.g., '{1, 2, 10} AS SAMPLE_TRIPID'.
    
    Returns:
    
    this to mimic the builder pattern.
  - getSolveMethod
```
public String getSolveMethod()
```
    Returns:
    The type of solver to use for graph matching. Supported values:
    
    MARKOV_CHAIN: Matches samplePoints to the graph using the Hidden Markov Model (HMM)-based method, which conducts a range-tree closest-edge search to find the best combinations of possible road segments (num_segments) for each sample point to create the best route. The route is secured one point at a time while looking ahead chain_width number of points, so the prediction is corrected after each point. This solution type is the most accurate but also the most computationally intensive. Related options: num_segments and chain_width.
    MATCH_OD_PAIRS: Matches samplePoints to find the most probable path between origin and destination pairs with cost constraints.
    MATCH_SUPPLY_DEMAND: Matches samplePoints to optimize scheduling multiple supplies (trucks) with varying sizes to varying demand sites with varying capacities per depot. Related options: partial_loading and max_combinations.
    MATCH_BATCH_SOLVES: Matches samplePoints source and destination pairs for the shortest path solves in batch mode.
    The default value is MARKOV_CHAIN.
  - setSolveMethod
```
public MatchGraphRequest setSolveMethod(String solveMethod)
```
    Parameters:
    solveMethod - The type of solver to use for graph matching. Supported values:
    
    MARKOV_CHAIN: Matches samplePoints to the graph using the Hidden Markov Model (HMM)-based method, which conducts a range-tree closest-edge search to find the best combinations of possible road segments (num_segments) for each sample point to create the best route. The route is secured one point at a time while looking ahead chain_width number of points, so the prediction is corrected after each point. This solution type is the most accurate but also the most computationally intensive. Related options: num_segments and chain_width.
    MATCH_OD_PAIRS: Matches samplePoints to find the most probable path between origin and destination pairs with cost constraints.
    MATCH_SUPPLY_DEMAND: Matches samplePoints to optimize scheduling multiple supplies (trucks) with varying sizes to varying demand sites with varying capacities per depot. Related options: partial_loading and max_combinations.
    MATCH_BATCH_SOLVES: Matches samplePoints source and destination pairs for the shortest path solves in batch mode.
    The default value is MARKOV_CHAIN.
    Returns:
    
    this to mimic the builder pattern.
  - getSolutionTable
```
public String getSolutionTable()
```
    Returns:
    
    The name of the table used to store the results; this table contains a track of geospatial points for the matched portion of the graph, a track ID, and a score value. Also outputs a details table containing a trip ID (that matches the track ID), the latitude/longitude pair, the timestamp the point was recorded at, and an edge ID corresponding to the matched road segment. Has the same naming restrictions as tables. Must not be an existing table of the same name. The default value is ''.
  - setSolutionTable
```
public MatchGraphRequest setSolutionTable(String solutionTable)
```
    Parameters:
    
    solutionTable - The name of the table used to store the results; this table contains a track of geospatial points for the matched portion of the graph, a track ID, and a score value. Also outputs a details table containing a trip ID (that matches the track ID), the latitude/longitude pair, the timestamp the point was recorded at, and an edge ID corresponding to the matched road segment. Has the same naming restrictions as tables. Must not be an existing table of the same name. The default value is ''.
    
    Returns:
    
    this to mimic the builder pattern.
  - getOptions
```
public Map<String,String> getOptions()
```
    Returns:
    Additional parameters
    
    GPS_NOISE: GPS noise value (in meters) to remove redundant sample points. Use -1 to disable noise reduction. The default value accounts for 95% of point variation (+ or -5 meters). The default value is '5.0'.
    NUM_SEGMENTS: Maximum number of potentially matching road segments for each sample point. For the markov_chain solver, the default is 3. The default value is '3'.
    SEARCH_RADIUS: Maximum search radius used when snapping sample points onto potentially matching surrounding segments. The default value corresponds to approximately 100 meters. The default value is '0.001'.
    CHAIN_WIDTH: For the markov_chain solver only. Length of the sample points lookahead window within the Markov kernel; the larger the number, the more accurate the solution. The default value is '9'.
    SOURCE: Optional WKT starting point from samplePoints for the solver. The default behavior for the endpoint is to use time to determine the starting point. The default value is 'POINT NULL'.
    DESTINATION: Optional WKT ending point from samplePoints for the solver. The default behavior for the endpoint is to use time to determine the destination point. The default value is 'POINT NULL'.
    PARTIAL_LOADING: For the match_supply_demand solver only. When false (non-default), trucks do not off-load at the demand (store) side if the remainder is less than the store's need Supported values:
    
    TRUE: Partial off-loading at multiple store (demand) locations
    FALSE: No partial off-loading allowed if supply is less than the store's demand.
    The default value is TRUE.
    MAX_COMBINATIONS: For the match_supply_demand solver only. This is the cutoff for the number of generated combinations for sequencing the demand locations - can increase this up to 2M. The default value is '10000'.
    LEFT_TURN_PENALTY: This will add an additonal weight over the edges labelled as 'left turn' if the 'add_turn' option parameter of the GPUdb.createGraph(CreateGraphRequest) was invoked at graph creation. The default value is '0.0'.
    RIGHT_TURN_PENALTY: This will add an additonal weight over the edges labelled as' right turn' if the 'add_turn' option parameter of the GPUdb.createGraph(CreateGraphRequest) was invoked at graph creation. The default value is '0.0'.
    INTERSECTION_PENALTY: This will add an additonal weight over the edges labelled as 'intersection' if the 'add_turn' option parameter of the GPUdb.createGraph(CreateGraphRequest) was invoked at graph creation. The default value is '0.0'.
    SHARP_TURN_PENALTY: This will add an additonal weight over the edges labelled as 'sharp turn' or 'u-turn' if the 'add_turn' option parameter of the GPUdb.createGraph(CreateGraphRequest) was invoked at graph creation. The default value is '0.0'.
    AGGREGATED_OUTPUT: For the match_supply_demand solver only. When it is true (default), each record in the output table shows a particular truck's scheduled cumulative round trip path (MULTILINESTRING) and the corresponding aggregated cost. Otherwise, each record shows a single scheduled truck route (LINESTRING) towards a particular demand location (store id) with its corresponding cost. The default value is 'true'.
    MAX_TRIP_COST: For the match_supply_demand solver only. If this constraint is greater than zero (default) then the trucks will skip travelling from one demand location to another if the cost between them is greater than this number (distance or time). Zero (default) value means no check is performed. The default value is '0.0'.
    FILTER_FOLDING_PATHS: For the markov_chain solver only. When true (non-default), the paths per sequence combination is checked for folding over patterns and can significantly increase the execution time depending on the chain width and the number of gps samples. Supported values:
    
    TRUE: Filter out the folded paths.
    FALSE: Do not filter out the folded paths
    The default value is FALSE.
    UNIT_UNLOADING_COST: For the match_supply_demand solver only. The unit cost per load amount to be delivered. If this value is greater than zero (default) then the additional cost of this unit load multiplied by the total dropped load will be added over to the trip cost to the demand location. The default value is '0.0'.
    MAX_NUM_THREADS: For the markov_chain solver only. If specified (greater than zero), the maximum number of threads will not be greater than the specified value. It can be lower due to the memory and the number cores available. Default value of zero allows the algorithm to set the maximal number of threads within these constraints. The default value is '0'.
    TRUCK_SERVICE_LIMIT: For the match_supply_demand solver only. If specified (greather than zero), any truck's total service cost (distance or time) will be limited by the specified value including multiple rounds (if set). The default value is '0.0'.
    ENABLE_TRUCK_REUSE: For the match_supply_demand solver only. If specified (true), all trucks can be scheduled for second rounds from their originating depots. Supported values:
    
    TRUE: Allows reusing trucks for scheduling again.
    FALSE: Trucks are scheduled only once from their depots.
    The default value is FALSE.
    The default value is an empty Map.
  - setOptions
```
public MatchGraphRequest setOptions(Map<String,String> options)
```
    Parameters:
    options - Additional parameters
    
    GPS_NOISE: GPS noise value (in meters) to remove redundant sample points. Use -1 to disable noise reduction. The default value accounts for 95% of point variation (+ or -5 meters). The default value is '5.0'.
    NUM_SEGMENTS: Maximum number of potentially matching road segments for each sample point. For the markov_chain solver, the default is 3. The default value is '3'.
    SEARCH_RADIUS: Maximum search radius used when snapping sample points onto potentially matching surrounding segments. The default value corresponds to approximately 100 meters. The default value is '0.001'.
    CHAIN_WIDTH: For the markov_chain solver only. Length of the sample points lookahead window within the Markov kernel; the larger the number, the more accurate the solution. The default value is '9'.
    SOURCE: Optional WKT starting point from samplePoints for the solver. The default behavior for the endpoint is to use time to determine the starting point. The default value is 'POINT NULL'.
    DESTINATION: Optional WKT ending point from samplePoints for the solver. The default behavior for the endpoint is to use time to determine the destination point. The default value is 'POINT NULL'.
    PARTIAL_LOADING: For the match_supply_demand solver only. When false (non-default), trucks do not off-load at the demand (store) side if the remainder is less than the store's need Supported values:
    
    TRUE: Partial off-loading at multiple store (demand) locations
    FALSE: No partial off-loading allowed if supply is less than the store's demand.
    The default value is TRUE.
    MAX_COMBINATIONS: For the match_supply_demand solver only. This is the cutoff for the number of generated combinations for sequencing the demand locations - can increase this up to 2M. The default value is '10000'.
    LEFT_TURN_PENALTY: This will add an additonal weight over the edges labelled as 'left turn' if the 'add_turn' option parameter of the GPUdb.createGraph(CreateGraphRequest) was invoked at graph creation. The default value is '0.0'.
    RIGHT_TURN_PENALTY: This will add an additonal weight over the edges labelled as' right turn' if the 'add_turn' option parameter of the GPUdb.createGraph(CreateGraphRequest) was invoked at graph creation. The default value is '0.0'.
    INTERSECTION_PENALTY: This will add an additonal weight over the edges labelled as 'intersection' if the 'add_turn' option parameter of the GPUdb.createGraph(CreateGraphRequest) was invoked at graph creation. The default value is '0.0'.
    SHARP_TURN_PENALTY: This will add an additonal weight over the edges labelled as 'sharp turn' or 'u-turn' if the 'add_turn' option parameter of the GPUdb.createGraph(CreateGraphRequest) was invoked at graph creation. The default value is '0.0'.
    AGGREGATED_OUTPUT: For the match_supply_demand solver only. When it is true (default), each record in the output table shows a particular truck's scheduled cumulative round trip path (MULTILINESTRING) and the corresponding aggregated cost. Otherwise, each record shows a single scheduled truck route (LINESTRING) towards a particular demand location (store id) with its corresponding cost. The default value is 'true'.
    MAX_TRIP_COST: For the match_supply_demand solver only. If this constraint is greater than zero (default) then the trucks will skip travelling from one demand location to another if the cost between them is greater than this number (distance or time). Zero (default) value means no check is performed. The default value is '0.0'.
    FILTER_FOLDING_PATHS: For the markov_chain solver only. When true (non-default), the paths per sequence combination is checked for folding over patterns and can significantly increase the execution time depending on the chain width and the number of gps samples. Supported values:
    
    TRUE: Filter out the folded paths.
    FALSE: Do not filter out the folded paths
    The default value is FALSE.
    UNIT_UNLOADING_COST: For the match_supply_demand solver only. The unit cost per load amount to be delivered. If this value is greater than zero (default) then the additional cost of this unit load multiplied by the total dropped load will be added over to the trip cost to the demand location. The default value is '0.0'.
    MAX_NUM_THREADS: For the markov_chain solver only. If specified (greater than zero), the maximum number of threads will not be greater than the specified value. It can be lower due to the memory and the number cores available. Default value of zero allows the algorithm to set the maximal number of threads within these constraints. The default value is '0'.
    TRUCK_SERVICE_LIMIT: For the match_supply_demand solver only. If specified (greather than zero), any truck's total service cost (distance or time) will be limited by the specified value including multiple rounds (if set). The default value is '0.0'.
    ENABLE_TRUCK_REUSE: For the match_supply_demand solver only. If specified (true), all trucks can be scheduled for second rounds from their originating depots. Supported values:
    
    TRUE: Allows reusing trucks for scheduling again.
    FALSE: Trucks are scheduled only once from their depots.
    The default value is FALSE.
    The default value is an empty Map.
    Returns:
    
    this to mimic the builder pattern.
  - getSchema
```
public org.apache.avro.Schema getSchema()
```
    This method supports the Avro framework and is not intended to be called directly by the user.
    
    Specified by:
    
    getSchema in interface org.apache.avro.generic.GenericContainer
    
    Returns:
    
    the schema object describing this class.
  - get
```
public Object get(int index)
```
    This method supports the Avro framework and is not intended to be called directly by the user.
    
    Specified by:
    
    get in interface org.apache.avro.generic.IndexedRecord
    
    Parameters:
    
    index - the position of the field to get
    
    Returns:
    
    value of the field with the given index.
    
    Throws:
    
    IndexOutOfBoundsException
  - put
```
public void put(int index,
                Object value)
```
    This method supports the Avro framework and is not intended to be called directly by the user.
    
    Specified by:
    
    put in interface org.apache.avro.generic.IndexedRecord
    
    Parameters:
    
    index - the position of the field to set
    
    value - the value to set
    
    Throws:
    
    IndexOutOfBoundsException
  - equals
```
public boolean equals(Object obj)
```
    Overrides:
    
    equals in class Object
  - toString
```
public String toString()
```
    Overrides:
    
    toString in class Object
  - hashCode
```
public int hashCode()
```
    Overrides:
    
    hashCode in class Object

Class MatchGraphRequest

Nested Class Summary

Constructor Summary

Method Summary

Methods inherited from class java.lang.Object

Constructor Detail

MatchGraphRequest

MatchGraphRequest

Method Detail

getClassSchema

getGraphName

setGraphName

getSamplePoints

setSamplePoints

getSolveMethod

setSolveMethod

getSolutionTable

setSolutionTable

getOptions

setOptions

getSchema

get

put

equals

toString

hashCode