}
  }

  /**
   * Returns the <a href="http://en.wikipedia.org/wiki/Filename_extension">file extension</a> for
   * the file at the given path, or the empty string if the file has no extension. The result does
   * not include the '{@code .}'.
   *
   * <p><b>Note:</b> This method simply returns everything after the last '{@code .}' in the file's

 *
 *  * The server's handshake certificates must have a [held certificate][HeldCertificate] (a
 *    certificate and its private key). The certificate's subject alternative names must match the
 *    server's hostname. The server must also have is a (possibly-empty) chain of intermediate
 *    certificates to establish trust from a root certificate to the server's certificate. The root
 *    certificate is not included in this chain.

   * bug</b> as described in the deprecation text.
   *
   * <p>The C++ equivalent is the MurmurHash3_x86_32 function (Murmur3A), which however does not
   * have the bug.
   *
   * @deprecated This implementation produces incorrect hash values from the {@link
   *     HashFunction#hashString} method if the string contains non-BMP characters. Use {@link

/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
 * with the License.  You may obtain a copy of the License at
 *

# vim: filetype=bash
#
# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

/*
 * Copyright 2012-2024 CodeLibs Project and the Others.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,

  if [[ ! -f $MINIO_ACCESSKEY_SECRETKEY_TMP ]];then
    echo "credentials file does not exist"
    return 1
  fi
  if [[ $(cat $MINIO_ACCESSKEY_SECRETKEY_TMP|wc -l) -ne 2 ]];then
    echo "credentials file is invalid"
    rm -f $MINIO_ACCESSKEY_SECRETKEY_TMP
    return 1
  fi
  USER=$(head -1 $MINIO_ACCESSKEY_SECRETKEY_TMP)
  # Create the user if it does not exist
  if ! checkUserExists ; then
    echo "Creating user '$USER'"

#!/usr/bin/env bash
#
# Copyright 2022 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

--from-file=keycloak.crt ``` If TLS is not enabled, you would need only the third party CA: ``` kubectl -n minio create secret generic minio-trusted-certs --from-file=keycloak.crt ``` The name of the generated secret can then be passed to Helm using a values file or the `--set` parameter: ``` trustedCertsSecret: "minio-trusted-certs" or --set trustedCertsSecret=minio-trusted-certs ``` Create buckets after install ---------- Install the chart, specifying the buckets you want to create after install: ```bash helm install...

   * data, and vertical if there is variance in the {@code y} data but not the {@code x} data.
   *
   * <p>This fit minimizes the root-mean-square error in {@code y} as a function of {@code x}. This
   * error is defined as the square root of the mean of the squares of the differences between the
   * actual {@code y} values of the data and the values predicted by the fit for the {@code x}