{"action":"created","comment":{"url":"https://api.github.com/repos/apache/parquet-mr/pulls/comments/138802138","pull_request_review_id":62642343,"id":138802138,"diff_hunk":"@@ -0,0 +1,485 @@\n+/*\n+ * Licensed to the Apache Software Foundation (ASF) under one\n+ * or more contributor license agreements.  See the NOTICE file\n+ * distributed with this work for additional information\n+ * regarding copyright ownership.  The ASF licenses this file\n+ * to you under the Apache License, Version 2.0 (the\n+ * \"License\"); you may not use this file except in compliance\n+ * with the License.  You may obtain a copy of the License at\n+ *\n+ *   http://www.apache.org/licenses/LICENSE-2.0\n+ *\n+ * Unless required by applicable law or agreed to in writing,\n+ * software distributed under the License is distributed on an\n+ * \"AS IS\" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY\n+ * KIND, either express or implied.  See the License for the\n+ * specific language governing permissions and limitations\n+ * under the License.\n+ */\n+package org.apache.parquet.column.values.bloom;\n+\n+import java.io.IOException;\n+import java.nio.ByteBuffer;\n+import java.nio.ByteOrder;\n+import java.util.ArrayList;\n+import java.util.Arrays;\n+import java.util.HashSet;\n+import java.util.List;\n+\n+import org.apache.parquet.Preconditions;\n+import org.apache.parquet.bytes.*;\n+import org.apache.parquet.column.Encoding;\n+import org.apache.parquet.column.ParquetProperties;\n+import org.apache.parquet.io.ParquetEncodingException;\n+import org.apache.parquet.io.api.Binary;\n+import org.apache.parquet.schema.PrimitiveType;\n+\n+/**\n+ * Bloom Filter is a compact structure to indicate whether an item is not in set or probably\n+ * in set. Bloom class is underlying class of Bloom Filter which stores a bit set represents\n+ * elements set, hash strategy and bloom filter algorithm.\n+ *\n+ * Bloom Filter algorithm is implemented using block Bloom filters from Putze et al.'s \"Cache-,\n+ * Hash- and Space-Efficient Bloom Filters\". The basic idea is to hash the item to a tiny Bloom\n+ * Filter which size fit a single cache line or smaller. This implementation sets 8 bits in\n+ * each tiny Bloom Filter. Tiny bloom filter are 32 bytes to take advantage of 32-bytes SIMD\n+ * instruction.\n+ */\n+\n+public abstract class Bloom<T extends Comparable<T>> {\n+  // Hash strategy available for bloom filter.\n+  public enum HASH {\n+    MURMUR3_X64_128,\n+  }\n+\n+  // Bloom filter algorithm.\n+  public enum ALGORITHM {\n+    BLOCK,\n+  }\n+\n+  /**\n+   * Default false positive probability value use to calculate optimal number of bits\n+   * used by bloom filter.\n+   */\n+  public final double FPP = 0.01;\n+\n+  // Bloom filter data header, including number of bytes, hash strategy and algorithm.\n+  public static final int BLOOM_HEADER_SIZE = 12;\n+\n+  // Bytes in a bucket.\n+  public static final int BYTES_PER_BUCKET = 32;\n+\n+  // Minimum bloom filter data size in byte.\n+  public static final int MINIMUM_BLOOM_SIZE = 256;\n+\n+  // Hash strategy used in this bloom filter.\n+  public HASH bloomFilterHash = HASH.MURMUR3_X64_128;\n+\n+  // Algorithm applied of this bloom filter.\n+  public ALGORITHM bloomFilterAlgorithm = ALGORITHM.BLOCK;\n+\n+  // A hash set to cache the distinct value from column.\n+  private HashSet<Long> elements = new HashSet<Long>();\n+\n+  // The underlying byte array for bloom filter bitset.\n+  private byte[] bitset;\n+\n+  // The size of bitset in byte.\n+  private int numBytes;\n+\n+  // List of byte input to construct the bloom filter.\n+  private final List<BytesInput> inputs= new ArrayList<>(4);\n+\n+  /**\n+   * Constructor of bloom filter, if numBytes is zero, bloom filter bitset\n+   * will be created lazily and the number of bytes will be calculated through\n+   * distinct values in cache.\n+   * @param numBytes The number of bytes for bloom filter bitset, set to zero can\n+   *                 let it calculate number automatically by using default FPP.\n+   * @param hash The hash strategy bloom filter apply.\n+   * @param algorithm The algorithm of bloom filter.\n+   */\n+  public Bloom(int numBytes, HASH hash, ALGORITHM algorithm) {\n+    if (numBytes != 0) {\n+      initBitset(numBytes);\n+    }\n+    this.bloomFilterHash = hash;\n+    this.bloomFilterAlgorithm = algorithm;\n+  }\n+\n+  /**\n+   * Construct the bloom filter with given bit set.\n+   * @param bitset The given bitset to construct bloom filter.\n+   * @param hash The hash strategy bloom filter apply.\n+   * @param algorithm The algorithm of bloom filter.\n+   */\n+  public Bloom(byte[] bitset, HASH hash, ALGORITHM algorithm) {\n+    this.bitset = bitset;\n+    this.numBytes = bitset.length;\n+    this.bloomFilterHash = hash;\n+    this.bloomFilterAlgorithm = algorithm;\n+  }\n+\n+  /**\n+   * Construct the bloom filter with given bit set.\n+   * @param input The given bitset to construct bloom filter.\n+   * @param hash The hash strategy bloom filter apply.\n+   * @param algorithm The algorithm of bloom filter.\n+   */\n+  public Bloom(ByteBuffer input, HASH hash, ALGORITHM algorithm) {\n+    if (input.isDirect()){\n+      bitset = new byte[input.remaining()];\n+      input.get(bitset);\n+    } else {\n+      this.bitset = input.array();\n+    }\n+    this.numBytes = input.array().length;\n+    this.bloomFilterHash = hash;\n+    this.bloomFilterAlgorithm = algorithm;\n+  }\n+\n+  /**\n+   * Create a new bitset for bloom filter, at least 256 bits will be create.\n+   * @param numBytes number of bytes for bit set.\n+   */\n+  private void initBitset(int numBytes) {\n+    if (numBytes < MINIMUM_BLOOM_SIZE) {\n+      numBytes = MINIMUM_BLOOM_SIZE;\n+    }\n+\n+    if (numBytes > ParquetProperties.DEFAULT_MAXIMUM_BLOOM_FILTER_SIZE) {\n+      numBytes = ParquetProperties.DEFAULT_MAXIMUM_BLOOM_FILTER_SIZE;\n+    }\n+\n+    // One bucket alignment.\n+    numBytes = (numBytes + BYTES_PER_BUCKET - 1) & ~(BYTES_PER_BUCKET - 1);\n+\n+    ByteBuffer bytes = ByteBuffer.allocate(numBytes);\n+    this.bitset = bytes.array();\n+    this.numBytes = numBytes;\n+  }\n+\n+  /**\n+   * @return Bytes in buffered in this bloom filter.\n+   */\n+  public BytesInput getBytes() {\n+    inputs.clear();\n+\n+    // Add number of bytes.\n+    inputs.add(BytesInput.fromInt(numBytes));\n+\n+    // Add hash strategy\n+    inputs.add(BytesInput.fromInt(this.bloomFilterHash.ordinal()));\n+\n+    // Add bloom filter algorithm\n+    inputs.add(BytesInput.fromInt(this.bloomFilterAlgorithm.ordinal()));\n+\n+    // Add bitset.\n+    inputs.add(BytesInput.from(bitset, 0, bitset.length));\n+\n+    return BytesInput.concat(inputs);\n+  }\n+\n+  private int[] setMask(int key) {\n+    // The block based algorithm needs 8 odd SALT values to calculate index\n+    // of bit to set in block.\n+    final int SALT[] = {0x47b6137b, 0x44974d91, 0x8824ad5b, 0xa2b7289d,\n+      0x705495c7, 0x2df1424b, 0x9efc4947, 0x5c6bfb31};\n+\n+    int mask[] = new int[8];\n+\n+    for (int i = 0; i < 8; ++i) {\n+      mask[i] = key * SALT[i];\n+    }\n+\n+    for (int i = 0; i < 8; ++i) {\n+      mask[i] = mask[i] >> 27;\n+    }\n+\n+    for (int i = 0; i < 8; ++i) {\n+      mask[i] = 0x1 << mask[i];\n+    }\n+\n+    return mask;\n+  }\n+\n+  /**\n+   * Add an element to bloom filter, the element content is represented by\n+   * the hash value of its plain encoding result.\n+   * @param hash hash result of element.\n+   */\n+  public void bloomInsert(long hash) {\n+    int bucketIndex = (int)(hash >> 32) & (numBytes / BYTES_PER_BUCKET - 1);\n+    int key = (int)hash;\n+\n+    // Calculate bit mask for bucket.\n+    int mask[] = setMask(key);\n+\n+    for (int i = 0; i < 8; i++) {\n+      int bitsetIndex = bucketIndex * BYTES_PER_BUCKET + i * 4;\n+      bitset[bitsetIndex] |= (byte)(mask[i] >>> 24);\n+      bitset[bitsetIndex + 1] |= (byte)(mask[i] >>> 16);\n+      bitset[bitsetIndex + 2] |= (byte)(mask[i] >>> 8);\n+      bitset[bitsetIndex + 3] |= (byte)(mask[i]);\n+    }\n+  }\n+\n+  /**\n+   * Determine where an element is in set or not.\n+   * @param hash the hash value of element plain encoding result.\n+   * @return false if element is must not in set, true if element probably in set.\n+   */\n+  public boolean bloomFind(long hash) {\n+    if (!elements.isEmpty()) {\n+      flush();\n+    }\n+\n+    int bucketIndex = (int)(hash >> 32) & (numBytes / BYTES_PER_BUCKET - 1);\n+    int key = (int)hash;\n+\n+    // Calculate bit mask for bucket.\n+    int mask[] = setMask(key);\n+\n+    for (int i = 0; i < 8; i++) {\n+      byte set = 0;\n+      int bitsetIndex = bucketIndex * BYTES_PER_BUCKET + i * 4;\n+      set |= bitset[bitsetIndex] & ((byte)(mask[i] >>> 24));\n+      set |= bitset[bitsetIndex + 1] & ((byte)(mask[i] >>> 16));\n+      set |= bitset[bitsetIndex + 2] & ((byte)(mask[i] >>> 8));\n+      set |= bitset[bitsetIndex + 3] & ((byte)mask[i]);\n+      if (0 == set) {\n+        return false;\n+      }\n+    }\n+\n+    return true;\n+  }\n+\n+  /**\n+   * Bloom filter bitset can be created lazily, flush() will set bits for\n+   * all elements in cache. If bitset was already created and set, it do nothing.\n+   */\n+  public void flush() {\n+    if (!elements.isEmpty() && bitset == null) {\n+      initBitset(optimalNumOfBits(elements.size(), FPP)/8);\n+      for (long hash : elements) {\n+        bloomInsert(hash);\n+      }\n+      elements.clear();\n+    }\n+  }\n+\n+  /**\n+   * Calculate optimal size according to the number of distinct values and false positive probability.\n+   * @param n: The number of distinct values.\n+   * @param p: The false positive probability.\n+   * @return optimal number of bits of given n and p.\n+   */\n+  public static int optimalNumOfBits(long n, double p) {\n+    Preconditions.checkArgument((p > 0.0 && p < 1.0),\n+      \"FPP should be less than 1.0 and great than 0.0\");\n+\n+    int bits = (int)(-n * Math.log(p) / (Math.log(2) * Math.log(2)));\n+\n+    // Get next power of 2 if bits is not power of 2.\n+    bits --;\n+    bits |= bits >> 1;\n+    bits |= bits >> 2;\n+    bits |= bits >> 4;\n+    bits |= bits >> 8;\n+    bits |= bits >> 16;\n+    bits++;\n+\n+    return bits;\n+  }\n+\n+  /**\n+   * @return Bytes buffered of bloom filter.\n+   */\n+  public long getBufferedSize() {\n+    return elements.size() * 8 + numBytes;\n+  }\n+\n+  /**\n+   * @return Bytes buffered of bloom filter.\n+   */\n+  public long getAllocatedSize() {\n+    return getBufferedSize();\n+  }\n+\n+  public String memUsageString(String prefix) 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don't see any callers","created_at":"2017-09-14T05:50:51Z","updated_at":"2017-09-14T05:52:43Z","html_url":"https://github.com/apache/parquet-mr/pull/425#discussion_r138802138","pull_request_url":"https://api.github.com/repos/apache/parquet-mr/pulls/425","author_association":"NONE","_links":{"self":{"href":"https://api.github.com/repos/apache/parquet-mr/pulls/comments/138802138"},"html":{"href":"https://github.com/apache/parquet-mr/pull/425#discussion_r138802138"},"pull_request":{"href":"https://api.github.com/repos/apache/parquet-mr/pulls/425"}}},"pull_request":{"url":"https://api.github.com/repos/apache/parquet-mr/pulls/425","id":139269267,"html_url":"https://github.com/apache/parquet-mr/pull/425","diff_url":"https://github.com/apache/parquet-mr/pull/425.diff","patch_url":"https://github.com/apache/parquet-mr/pull/425.patch","issue_url":"https://api.github.com/repos/apache/parquet-mr/issues/425","number":425,"state":"open","locked":false,"title":"PARQUET-41:Add Bloom Filter for parquet","user":{"login":"cjjnjust","id":3960228,"avatar_url":"https://avatars1.githubusercontent.com/u/3960228?v=4","gravatar_id":"","url":"https://api.github.com/users/cjjnjust","html_url":"https://github.com/cjjnjust","followers_url":"https://api.github.com/users/cjjnjust/followers","following_url":"https://api.github.com/users/cjjnjust/following{/other_user}","gists_url":"https://api.github.com/users/cjjnjust/gists{/gist_id}","starred_url":"https://api.github.com/users/cjjnjust/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/cjjnjust/subscriptions","organizations_url":"https://api.github.com/users/cjjnjust/orgs","repos_url":"https://api.github.com/users/cjjnjust/repos","events_url":"https://api.github.com/users/cjjnjust/events{/privacy}","received_events_url":"https://api.github.com/users/cjjnjust/received_events","type":"User","site_admin":false},"body":"This is an initial patch just include bloom filter itself.\r\n\r\n\r\n","created_at":"2017-09-05T08:52:23Z","updated_at":"2017-09-14T05:52:43Z","closed_at":null,"merged_at":null,"merge_commit_sha":"f790f4649b78ee1767d006faf4cf089b34404e39","assignee":null,"assignees":[],"requested_reviewers":[],"milestone":null,"commits_url":"https://api.github.com/repos/apache/parquet-mr/pulls/425/commits","review_comments_url":"https://api.github.com/repos/apache/parquet-mr/pulls/425/comments","review_comment_url":"https://api.github.com/repos/apache/parquet-mr/pulls/comments{/number}","comments_url":"https://api.github.com/repos/apache/parquet-mr/issues/425/comments","statuses_url":"https://api.github.com/repos/apache/parquet-mr/statuses/9bf76bdf588d9a2c4b770c4db85df4560b846aa2","head":{"label":"cjjnjust:parquet-41","ref":"parquet-41","sha":"9bf76bdf588d9a2c4b770c4db85df4560b846aa2","user":{"login":"cjjnjust","id":3960228,"avatar_url":"https://avatars1.githubusercontent.com/u/3960228?v=4","gravatar_id":"","url":"https://api.github.com/users/cjjnjust","html_url":"https://github.com/cjjnjust","followers_url":"https://api.github.com/users/cjjnjust/followers","following_url":"https://api.github.com/users/cjjnjust/following{/other_user}","gists_url":"https://api.github.com/users/cjjnjust/gists{/gist_id}","starred_url":"https://api.github.com/users/cjjnjust/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/cjjnjust/subscriptions","organizations_url":"https://api.github.com/users/cjjnjust/orgs","repos_url":"https://api.github.com/users/cjjnjust/repos","events_url":"https://api.github.com/users/cjjnjust/events{/privacy}","received_events_url":"https://api.github.com/users/cjjnjust/received_events","type":"User","site_admin":false},"repo":{"id":101361250,"name":"parquet-mr","full_name":"cjjnjust/parquet-mr","owner":{"login":"cjjnjust","id":3960228,"avatar_url":"https://avatars1.githubusercontent.com/u/3960228?v=4","gravatar_id":"","url":"https://api.github.com/users/cjjnjust","html_url":"https://github.com/cjjnjust","followers_url":"https://api.github.com/users/cjjnjust/followers","following_url":"https://api.github.com/users/cjjnjust/following{/other_user}","gists_url":"https://api.github.com/users/cjjnjust/gists{/gist_id}","starred_url":"https://api.github.com/users/cjjnjust/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/cjjnjust/subscriptions","organizations_url":"https://api.github.com/users/cjjnjust/orgs","repos_url":"https://api.github.com/users/cjjnjust/repos","events_url":"https://api.github.com/users/cjjnjust/events{/privacy}","received_events_url":"https://api.github.com/users/cjjnjust/received_events","type":"User","site_admin":false},"private":false,"html_url":"https://github.com/cjjnjust/parquet-mr","description":"Mirror 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