Hi i am new with graphhopper and i want to use custom profile but when I set my profile i get the error
java.lang.IllegalArgumentException: CH preparation of my_car_profile already exists in storage and doesn't match configuration.
Here is my config.yml
graphhopper:
# OpenStreetMap input file
datareader.file: bulgaria-latest.osm.pbf
# OpenStreetMap cache location
graph.location: ./data
##### Vehicles #####
# More options: foot,bike,bike2,mtb,racingbike,motorcycle (comma separated)
# bike2 takes elevation data into account (like up-hill is slower than down-hill) and requires enabling graph.elevation.provider below.
graph.flag_encoders: car|turn_costs=true|speed_two_directions=true
# Enable turn restrictions for car or motorcycle.
# graph.flag_encoders: car|turn_costs=true
# Add additional information to every edge. Used for path details.
# If road_environment is added and elevation is enabled then also a tunnel and bridge interpolation is done, see #798.
# More options are: surface,max_width,max_height,max_weight,max_axle_load,max_length,hazmat,hazmat_water,toll,track_type
graph.encoded_values: surface,road_class,road_class_link,road_environment,max_speed,road_access
graph.bytes_for_flags: 8
##### Elevation #####
# To populate your graph with elevation data use SRTM, default is noop (no elevation)
# graph.elevation.provider: srtm
# default location for cache is /tmp/srtm
# graph.elevation.cache_dir: ./srtmprovider/
# If you have a slow disk or plenty of RAM change the default MMAP to:
# graph.elevation.dataaccess: RAM_STORE
#### Speed, hybrid and flexible mode ####
# Disable the speed mode. Should be used only with routing.max_visited_nodes or when the hybrid mode is enabled instead
# prepare.ch.weightings: no
# To make CH preparation faster for multiple flagEncoders you can increase the default threads if you have enough RAM.
# Change this setting only if you know what you are doing and if the default worked for you.
# prepare.ch.threads: 1
# The hybrid mode can be enabled with
# prepare.lm.weightings: fastest
# To tune the performance vs. memory usage for the hybrid mode use
# prepare.lm.landmarks: 16
# Make landmark preparation parallel if you have enough RAM. Change this only if you know what you are doing and if the default worked for you.
# prepare.lm.threads: 1
# avoid being stuck in a (oneway) subnetwork, see https://discuss.graphhopper.com/t/93
prepare.min_network_size: 200
prepare.min_one_way_network_size: 200
##### Routing #####
# You can define the maximum visited nodes when routing. This may result in not found connections if there is no
# connection between two points within the given visited nodes. The default is Integer.MAX_VALUE. Useful for flexibility mode
# routing.max_visited_nodes: 1000000
# If enabled, allows a user to run flexibility requests even if speed mode is enabled. Every request then has to include a hint ch.disable=true.
# Attention, non-CH route calculations take way more time and resources, compared to CH routing.
# A possible attacker might exploit this to slow down your service. Only enable it if you need it and with routing.maxVisitedNodes
# routing.ch.disabling_allowed: true
# If enabled, allows a user to run flexible mode requests even if the hybrid mode is enabled. Every such request then has to include a hint routing.lm.disable=true.
# routing.lm.disabling_allowed: true
# Control how many active landmarks are picked per default, this can improve query performance
# routing.lm.active_landmarks: 4
##### Routing Profiles ####
# See https://github.com/graphhopper/graphhopper/blob/master/docs/core/profiles.md
# Routing can be done for the following list of profiles. Note that it is required to specify all the profiles you
# would like to use here. The fields of each profile are as follows:
# - name (required): a unique string identifier for the profile
# - vehicle (required): refers to the `graph.flag_encoders` used for this profile
# - weighting (required): the weighting used for this profile, e.g. fastest,shortest or short_fastest
# - turn_costs (true/false, default: false): whether or not turn restrictions should be applied for this profile.
# this will only work if the `graph.flag_encoders` for the given `vehicle` is configured with `|turn_costs=true`.
#
# Depending on the above fields there are other properties that can be used, e.g.
# - distance_factor: 0.1 (can be used to fine tune the time/distance trade-off of short_fastest weighting)
# - u_turn_costs: 60 (time-penalty for doing a u-turn in seconds (only possible when `turn_costs: true`)).
# Note that since the u-turn costs are given in seconds the weighting you use should also calculate the weight
# in seconds, so for example it does not work with shortest weighting.
# - custom_model_file: when you specified "weighting: custom" you need to set a yaml file that defines the custom_model.
# If you want an empty model you can also set "custom_model_file: empty".
#
# For more information about profiles and especially custom profiles have a look into the documentation
# at docs/core/profiles.md or the examples under web/src/test/resources/com/graphhopper/http/resources/ or
# the CustomWeighting class for the raw details.
#
# To prevent long running routing queries you should usually enable either speed or hybrid mode for all the given
# profiles (see below). Otherwise you should at least limit the number of `routing.max_visited_nodes`.
profiles:
- name: my_car_profile
vehicle: car
weighting: custom
custom_model_file: car_profile.yml
# Speed mode:
# Its possible to speed up routing by doing a special graph preparation (Contraction Hierarchies, CH). This requires
# more RAM/disk space for holding the prepared graph but also means less memory usage per request. Using the following
# list you can define for which of the above routing profiles such preparation shall be performed. Note that to support
# profiles with `turn_costs: true` a more elaborate preparation is required (longer preparation time and more memory
# usage) and the routing will also be slower than with `turn_costs: false`.
profiles_ch:
- profile: my_car_profile
# Hybrid mode:
# Similar to speed mode, the hybrid mode (Landmarks, LM) also speeds up routing by doing calculating auxiliary data
# in advance. Its not as fast as speed mode, but more flexible.
#
# Advanced usage: It is possible to use the same preparation for multiple profiles which saves memory and preparation
# time. To do this use e.g. `preparation_profile: my_other_profile` where `my_other_profile` is the name of another
# profile for which an LM profile exists. Important: This only will give correct routing results if the weights
# calculated for the profile are equal or larger (for every edge) than those calculated for the profile that was used
# for the preparation (`my_other_profile`)
profiles_lm: []
# - profile: my_car_profile
# You can limit the max distance between two consecutive waypoints of flexible routing requests to be less or equal
# the given distance in meter. Default is set to 1000km.
routing.non_ch.max_waypoint_distance: 1000000
##### Storage #####
# configure the memory access, use RAM_STORE for well equipped servers (default and recommended)
graph.dataaccess: RAM_STORE
# will write way names in the preferred language (language code as defined in ISO 639-1 or ISO 639-2):
# datareader.preferred_language: en
# Sort the graph after import to make requests roughly ~10% faster. Note that this requires significantly more RAM on import.
# graph.do_sort: true
##### Spatial Rules #####
# Spatial Rules require some configuration and only work with the DataFlagEncoder.
# Spatial Rules require you to provide Polygons in which the rules are enforced
# The line below contains the default location for these rules
# spatial_rules.location: core/files/spatialrules/countries.geo.json
# You can define the maximum BBox for which spatial rules are loaded.
# You might want to do this if you are only importing a small area and don't need rules for other countries.
# Having less rules, might result in a smaller graph. The line below contains the world-wide bounding box, uncomment and adapt to your need.
# spatial_rules.max_bbox: -180,180,-90,90
# Uncomment the following to point /maps to the source directory in the filesystem instead of
# the Java resource path. Helpful for development of the web client.
# Assumes that the web module is the working directory.
#
# assets:
# overrides:
# /maps: web/src/main/resources/assets/
# Dropwizard server configuration
server:
application_connectors:
- type: http
port: 8989
- type: http
port: 6060
request_log:
appenders: []
admin_connectors:
- type: http
port: 8990
bind_host: localhost
# See https://www.dropwizard.io/1.3.8/docs/manual/configuration.html#logging
logging:
appenders:
- type: file
time_zone: UTC
current_log_filename: logs/graphhopper.log
log_format: "%d{YYYY-MM-dd HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n"
archive: true
archived_log_filename_pattern: ./logs/graphhopper-%d.log.gz
archived_file_count: 30
never_block: true
- type: console
time_zone: UTC
log_format: "%d{YYYY-MM-dd HH:mm:ss.SSS} [%thread] %-5level %logger{36} - %msg%n"
Here is my car_profile.yml
priority:
road_class: { primary: 1, secondary: 1, trunk: 1, tertiary: 1, residential: 0.2,unclassified: 0.2}`Preformatted text`