Package io.envoyproxy.envoy.extensions.load_balancing_policies.common.v3

Class ConsistentHashingLbConfig.Builder

  • All Implemented Interfaces:
    com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, ConsistentHashingLbConfigOrBuilder, java.lang.Cloneable
    Enclosing class:
    ConsistentHashingLbConfig
    public static final class ConsistentHashingLbConfig.Builder
extends com.google.protobuf.GeneratedMessage.Builder<ConsistentHashingLbConfig.Builder>
implements ConsistentHashingLbConfigOrBuilder
     Common Configuration for all consistent hashing load balancers (MaglevLb, RingHashLb, etc.)
    Protobuf type envoy.extensions.load_balancing_policies.common.v3.ConsistentHashingLbConfig

    • Field Detail

      • bitField0_

        private int bitField0_

      • useHostnameForHashing_

        private boolean useHostnameForHashing_

      • hashBalanceFactor_

        private com.google.protobuf.UInt32Value hashBalanceFactor_

      • hashBalanceFactorBuilder_

        private com.google.protobuf.SingleFieldBuilder<com.google.protobuf.UInt32Value,​com.google.protobuf.UInt32Value.Builder,​com.google.protobuf.UInt32ValueOrBuilder> hashBalanceFactorBuilder_

    • Constructor Detail

      • Builder

        private Builder()

      • Builder

        private Builder​(com.google.protobuf.AbstractMessage.BuilderParent parent)

    • Method Detail

      • getDescriptor

        public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<ConsistentHashingLbConfig.Builder>

      • maybeForceBuilderInitialization

        private void maybeForceBuilderInitialization()

      • getDescriptorForType

        public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
        Specified by:
        getDescriptorForType in interface com.google.protobuf.Message.Builder
        Specified by:
        getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
        Overrides:
        getDescriptorForType in class com.google.protobuf.GeneratedMessage.Builder<ConsistentHashingLbConfig.Builder>

      • getDefaultInstanceForType

        public ConsistentHashingLbConfig getDefaultInstanceForType()
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
        Specified by:
        getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

      • build

        public ConsistentHashingLbConfig build()
        Specified by:
        build in interface com.google.protobuf.Message.Builder
        Specified by:
        build in interface com.google.protobuf.MessageLite.Builder

      • buildPartial

        public ConsistentHashingLbConfig buildPartial()
        Specified by:
        buildPartial in interface com.google.protobuf.Message.Builder
        Specified by:
        buildPartial in interface com.google.protobuf.MessageLite.Builder

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class com.google.protobuf.GeneratedMessage.Builder<ConsistentHashingLbConfig.Builder>

      • mergeFrom

        public ConsistentHashingLbConfig.Builder mergeFrom​(com.google.protobuf.CodedInputStream input,
                                                   com.google.protobuf.ExtensionRegistryLite extensionRegistry)
                                            throws java.io.IOException
        Specified by:
        mergeFrom in interface com.google.protobuf.Message.Builder
        Specified by:
        mergeFrom in interface com.google.protobuf.MessageLite.Builder
        Overrides:
        mergeFrom in class com.google.protobuf.AbstractMessage.Builder<ConsistentHashingLbConfig.Builder>
        Throws:
        java.io.IOException

      • getUseHostnameForHashing

        public boolean getUseHostnameForHashing()
         If set to ``true``, the cluster will use hostname instead of the resolved
 address as the key to consistently hash to an upstream host. Only valid for StrictDNS clusters with hostnames which resolve to a single IP address.
        bool use_hostname_for_hashing = 1;
        Specified by:
        getUseHostnameForHashing in interface ConsistentHashingLbConfigOrBuilder
        Returns:
        The useHostnameForHashing.

      • setUseHostnameForHashing

        public ConsistentHashingLbConfig.Builder setUseHostnameForHashing​(boolean value)
         If set to ``true``, the cluster will use hostname instead of the resolved
 address as the key to consistently hash to an upstream host. Only valid for StrictDNS clusters with hostnames which resolve to a single IP address.
        bool use_hostname_for_hashing = 1;
        Parameters:
        value - The useHostnameForHashing to set.
        Returns:
        This builder for chaining.

      • clearUseHostnameForHashing

        public ConsistentHashingLbConfig.Builder clearUseHostnameForHashing()
         If set to ``true``, the cluster will use hostname instead of the resolved
 address as the key to consistently hash to an upstream host. Only valid for StrictDNS clusters with hostnames which resolve to a single IP address.
        bool use_hostname_for_hashing = 1;
        Returns:
        This builder for chaining.

      • hasHashBalanceFactor

        public boolean hasHashBalanceFactor()
         Configures percentage of average cluster load to bound per upstream host. For example, with a value of 150
 no upstream host will get a load more than 1.5 times the average load of all the hosts in the cluster.
 If not specified, the load is not bounded for any upstream host. Typical value for this parameter is between 120 and 200.
 Minimum is 100.

 Applies to both Ring Hash and Maglev load balancers.

 This is implemented based on the method described in the paper https://arxiv.org/abs/1608.01350. For the specified
 ``hash_balance_factor``, requests to any upstream host are capped at ``hash_balance_factor/100`` times the average number of requests
 across the cluster. When a request arrives for an upstream host that is currently serving at its max capacity, linear probing
 is used to identify an eligible host. Further, the linear probe is implemented using a random jump in hosts ring/table to identify
 the eligible host (this technique is as described in the paper https://arxiv.org/abs/1908.08762 - the random jump avoids the
 cascading overflow effect when choosing the next host in the ring/table).

 If weights are specified on the hosts, they are respected.

 This is an O(N) algorithm, unlike other load balancers. Using a lower ``hash_balance_factor`` results in more hosts
 being probed, so use a higher value if you require better performance.
        .google.protobuf.UInt32Value hash_balance_factor = 2 [(.validate.rules) = { ... }
        Specified by:
        hasHashBalanceFactor in interface ConsistentHashingLbConfigOrBuilder
        Returns:
        Whether the hashBalanceFactor field is set.

      • getHashBalanceFactor

        public com.google.protobuf.UInt32Value getHashBalanceFactor()
         Configures percentage of average cluster load to bound per upstream host. For example, with a value of 150
 no upstream host will get a load more than 1.5 times the average load of all the hosts in the cluster.
 If not specified, the load is not bounded for any upstream host. Typical value for this parameter is between 120 and 200.
 Minimum is 100.

 Applies to both Ring Hash and Maglev load balancers.

 This is implemented based on the method described in the paper https://arxiv.org/abs/1608.01350. For the specified
 ``hash_balance_factor``, requests to any upstream host are capped at ``hash_balance_factor/100`` times the average number of requests
 across the cluster. When a request arrives for an upstream host that is currently serving at its max capacity, linear probing
 is used to identify an eligible host. Further, the linear probe is implemented using a random jump in hosts ring/table to identify
 the eligible host (this technique is as described in the paper https://arxiv.org/abs/1908.08762 - the random jump avoids the
 cascading overflow effect when choosing the next host in the ring/table).

 If weights are specified on the hosts, they are respected.

 This is an O(N) algorithm, unlike other load balancers. Using a lower ``hash_balance_factor`` results in more hosts
 being probed, so use a higher value if you require better performance.
        .google.protobuf.UInt32Value hash_balance_factor = 2 [(.validate.rules) = { ... }
        Specified by:
        getHashBalanceFactor in interface ConsistentHashingLbConfigOrBuilder
        Returns:
        The hashBalanceFactor.

      • setHashBalanceFactor

        public ConsistentHashingLbConfig.Builder setHashBalanceFactor​(com.google.protobuf.UInt32Value value)
         Configures percentage of average cluster load to bound per upstream host. For example, with a value of 150
 no upstream host will get a load more than 1.5 times the average load of all the hosts in the cluster.
 If not specified, the load is not bounded for any upstream host. Typical value for this parameter is between 120 and 200.
 Minimum is 100.

 Applies to both Ring Hash and Maglev load balancers.

 This is implemented based on the method described in the paper https://arxiv.org/abs/1608.01350. For the specified
 ``hash_balance_factor``, requests to any upstream host are capped at ``hash_balance_factor/100`` times the average number of requests
 across the cluster. When a request arrives for an upstream host that is currently serving at its max capacity, linear probing
 is used to identify an eligible host. Further, the linear probe is implemented using a random jump in hosts ring/table to identify
 the eligible host (this technique is as described in the paper https://arxiv.org/abs/1908.08762 - the random jump avoids the
 cascading overflow effect when choosing the next host in the ring/table).

 If weights are specified on the hosts, they are respected.

 This is an O(N) algorithm, unlike other load balancers. Using a lower ``hash_balance_factor`` results in more hosts
 being probed, so use a higher value if you require better performance.
        .google.protobuf.UInt32Value hash_balance_factor = 2 [(.validate.rules) = { ... }

      • setHashBalanceFactor

        public ConsistentHashingLbConfig.Builder setHashBalanceFactor​(com.google.protobuf.UInt32Value.Builder builderForValue)
         Configures percentage of average cluster load to bound per upstream host. For example, with a value of 150
 no upstream host will get a load more than 1.5 times the average load of all the hosts in the cluster.
 If not specified, the load is not bounded for any upstream host. Typical value for this parameter is between 120 and 200.
 Minimum is 100.

 Applies to both Ring Hash and Maglev load balancers.

 This is implemented based on the method described in the paper https://arxiv.org/abs/1608.01350. For the specified
 ``hash_balance_factor``, requests to any upstream host are capped at ``hash_balance_factor/100`` times the average number of requests
 across the cluster. When a request arrives for an upstream host that is currently serving at its max capacity, linear probing
 is used to identify an eligible host. Further, the linear probe is implemented using a random jump in hosts ring/table to identify
 the eligible host (this technique is as described in the paper https://arxiv.org/abs/1908.08762 - the random jump avoids the
 cascading overflow effect when choosing the next host in the ring/table).

 If weights are specified on the hosts, they are respected.

 This is an O(N) algorithm, unlike other load balancers. Using a lower ``hash_balance_factor`` results in more hosts
 being probed, so use a higher value if you require better performance.
        .google.protobuf.UInt32Value hash_balance_factor = 2 [(.validate.rules) = { ... }

      • mergeHashBalanceFactor

        public ConsistentHashingLbConfig.Builder mergeHashBalanceFactor​(com.google.protobuf.UInt32Value value)
         Configures percentage of average cluster load to bound per upstream host. For example, with a value of 150
 no upstream host will get a load more than 1.5 times the average load of all the hosts in the cluster.
 If not specified, the load is not bounded for any upstream host. Typical value for this parameter is between 120 and 200.
 Minimum is 100.

 Applies to both Ring Hash and Maglev load balancers.

 This is implemented based on the method described in the paper https://arxiv.org/abs/1608.01350. For the specified
 ``hash_balance_factor``, requests to any upstream host are capped at ``hash_balance_factor/100`` times the average number of requests
 across the cluster. When a request arrives for an upstream host that is currently serving at its max capacity, linear probing
 is used to identify an eligible host. Further, the linear probe is implemented using a random jump in hosts ring/table to identify
 the eligible host (this technique is as described in the paper https://arxiv.org/abs/1908.08762 - the random jump avoids the
 cascading overflow effect when choosing the next host in the ring/table).

 If weights are specified on the hosts, they are respected.

 This is an O(N) algorithm, unlike other load balancers. Using a lower ``hash_balance_factor`` results in more hosts
 being probed, so use a higher value if you require better performance.
        .google.protobuf.UInt32Value hash_balance_factor = 2 [(.validate.rules) = { ... }

      • clearHashBalanceFactor

        public ConsistentHashingLbConfig.Builder clearHashBalanceFactor()
         Configures percentage of average cluster load to bound per upstream host. For example, with a value of 150
 no upstream host will get a load more than 1.5 times the average load of all the hosts in the cluster.
 If not specified, the load is not bounded for any upstream host. Typical value for this parameter is between 120 and 200.
 Minimum is 100.

 Applies to both Ring Hash and Maglev load balancers.

 This is implemented based on the method described in the paper https://arxiv.org/abs/1608.01350. For the specified
 ``hash_balance_factor``, requests to any upstream host are capped at ``hash_balance_factor/100`` times the average number of requests
 across the cluster. When a request arrives for an upstream host that is currently serving at its max capacity, linear probing
 is used to identify an eligible host. Further, the linear probe is implemented using a random jump in hosts ring/table to identify
 the eligible host (this technique is as described in the paper https://arxiv.org/abs/1908.08762 - the random jump avoids the
 cascading overflow effect when choosing the next host in the ring/table).

 If weights are specified on the hosts, they are respected.

 This is an O(N) algorithm, unlike other load balancers. Using a lower ``hash_balance_factor`` results in more hosts
 being probed, so use a higher value if you require better performance.
        .google.protobuf.UInt32Value hash_balance_factor = 2 [(.validate.rules) = { ... }

      • getHashBalanceFactorBuilder

        public com.google.protobuf.UInt32Value.Builder getHashBalanceFactorBuilder()
         Configures percentage of average cluster load to bound per upstream host. For example, with a value of 150
 no upstream host will get a load more than 1.5 times the average load of all the hosts in the cluster.
 If not specified, the load is not bounded for any upstream host. Typical value for this parameter is between 120 and 200.
 Minimum is 100.

 Applies to both Ring Hash and Maglev load balancers.

 This is implemented based on the method described in the paper https://arxiv.org/abs/1608.01350. For the specified
 ``hash_balance_factor``, requests to any upstream host are capped at ``hash_balance_factor/100`` times the average number of requests
 across the cluster. When a request arrives for an upstream host that is currently serving at its max capacity, linear probing
 is used to identify an eligible host. Further, the linear probe is implemented using a random jump in hosts ring/table to identify
 the eligible host (this technique is as described in the paper https://arxiv.org/abs/1908.08762 - the random jump avoids the
 cascading overflow effect when choosing the next host in the ring/table).

 If weights are specified on the hosts, they are respected.

 This is an O(N) algorithm, unlike other load balancers. Using a lower ``hash_balance_factor`` results in more hosts
 being probed, so use a higher value if you require better performance.
        .google.protobuf.UInt32Value hash_balance_factor = 2 [(.validate.rules) = { ... }

      • getHashBalanceFactorOrBuilder

        public com.google.protobuf.UInt32ValueOrBuilder getHashBalanceFactorOrBuilder()
         Configures percentage of average cluster load to bound per upstream host. For example, with a value of 150
 no upstream host will get a load more than 1.5 times the average load of all the hosts in the cluster.
 If not specified, the load is not bounded for any upstream host. Typical value for this parameter is between 120 and 200.
 Minimum is 100.

 Applies to both Ring Hash and Maglev load balancers.

 This is implemented based on the method described in the paper https://arxiv.org/abs/1608.01350. For the specified
 ``hash_balance_factor``, requests to any upstream host are capped at ``hash_balance_factor/100`` times the average number of requests
 across the cluster. When a request arrives for an upstream host that is currently serving at its max capacity, linear probing
 is used to identify an eligible host. Further, the linear probe is implemented using a random jump in hosts ring/table to identify
 the eligible host (this technique is as described in the paper https://arxiv.org/abs/1908.08762 - the random jump avoids the
 cascading overflow effect when choosing the next host in the ring/table).

 If weights are specified on the hosts, they are respected.

 This is an O(N) algorithm, unlike other load balancers. Using a lower ``hash_balance_factor`` results in more hosts
 being probed, so use a higher value if you require better performance.
        .google.protobuf.UInt32Value hash_balance_factor = 2 [(.validate.rules) = { ... }
        Specified by:
        getHashBalanceFactorOrBuilder in interface ConsistentHashingLbConfigOrBuilder

      • getHashBalanceFactorFieldBuilder

        private com.google.protobuf.SingleFieldBuilder<com.google.protobuf.UInt32Value,​com.google.protobuf.UInt32Value.Builder,​com.google.protobuf.UInt32ValueOrBuilder> getHashBalanceFactorFieldBuilder()
         Configures percentage of average cluster load to bound per upstream host. For example, with a value of 150
 no upstream host will get a load more than 1.5 times the average load of all the hosts in the cluster.
 If not specified, the load is not bounded for any upstream host. Typical value for this parameter is between 120 and 200.
 Minimum is 100.

 Applies to both Ring Hash and Maglev load balancers.

 This is implemented based on the method described in the paper https://arxiv.org/abs/1608.01350. For the specified
 ``hash_balance_factor``, requests to any upstream host are capped at ``hash_balance_factor/100`` times the average number of requests
 across the cluster. When a request arrives for an upstream host that is currently serving at its max capacity, linear probing
 is used to identify an eligible host. Further, the linear probe is implemented using a random jump in hosts ring/table to identify
 the eligible host (this technique is as described in the paper https://arxiv.org/abs/1908.08762 - the random jump avoids the
 cascading overflow effect when choosing the next host in the ring/table).

 If weights are specified on the hosts, they are respected.

 This is an O(N) algorithm, unlike other load balancers. Using a lower ``hash_balance_factor`` results in more hosts
 being probed, so use a higher value if you require better performance.
        .google.protobuf.UInt32Value hash_balance_factor = 2 [(.validate.rules) = { ... }