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https://issues.apache.org/jira/browse/PARQUET-2254?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17717544#comment-17717544
 ] 

ASF GitHub Bot commented on PARQUET-2254:
-----------------------------------------

yabola commented on code in PR #1042:
URL: https://github.com/apache/parquet-mr/pull/1042#discussion_r1180115504


##########
parquet-column/src/main/java/org/apache/parquet/column/values/bloomfilter/DynamicBlockBloomFilter.java:
##########
@@ -0,0 +1,314 @@
+/*
+ * 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
+ *
+ *   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, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied.  See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+
+package org.apache.parquet.column.values.bloomfilter;
+
+import static 
org.apache.parquet.column.values.bloomfilter.BlockSplitBloomFilter.LOWER_BOUND_BYTES;
+import static 
org.apache.parquet.column.values.bloomfilter.BlockSplitBloomFilter.UPPER_BOUND_BYTES;
+
+import java.io.IOException;
+import java.io.OutputStream;
+import java.util.ArrayList;
+import java.util.Arrays;
+import java.util.List;
+import java.util.Objects;
+import java.util.Optional;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+import org.apache.parquet.Preconditions;
+import org.apache.parquet.column.ColumnDescriptor;
+import org.apache.parquet.io.api.Binary;
+
+/**
+ * `DynamicBlockBloomFilter` contains multiple `BlockSplitBloomFilter` as 
candidates and inserts values in
+ * the candidates at the same time.
+ * The purpose of this is to finally generate a bloom filter with the optimal 
bit size according to the number
+ * of real data distinct values. Use the largest bloom filter as an 
approximate deduplication counter, and then
+ * remove incapable bloom filter candidate during data insertion.
+ */
+public class DynamicBlockBloomFilter implements BloomFilter {
+
+  private static final Logger LOG = 
LoggerFactory.getLogger(DynamicBlockBloomFilter.class);
+
+  // multiple candidates, inserting data at the same time. If the distinct 
values are greater than the
+  // expected NDV of candidates, it will be removed. Finally we will choose 
the smallest candidate to write out.
+  private final List<BloomFilterCandidate> candidates = new ArrayList<>();
+
+  // the largest among candidates and used as an approximate deduplication 
counter
+  private BloomFilterCandidate maxCandidate;
+
+  // the accumulator of the number of distinct values that have been inserted 
so far
+  private int distinctValueCounter = 0;

Review Comment:
   I changed to use `long`





> Build a BloomFilter with a more precise size
> --------------------------------------------
>
>                 Key: PARQUET-2254
>                 URL: https://issues.apache.org/jira/browse/PARQUET-2254
>             Project: Parquet
>          Issue Type: Improvement
>            Reporter: Mars
>            Assignee: Mars
>            Priority: Major
>
> h3. Why are the changes needed?
> Now the usage of bloom filter is to specify the NDV(number of distinct 
> values), and then build BloomFilter. In general scenarios, it is actually not 
> sure how much the distinct value is.
> If BloomFilter can be automatically generated according to the data, the file 
> size can be reduced and the reading efficiency can also be improved.
> h3. What changes were proposed in this pull request?
> {{DynamicBlockBloomFilter}} contains multiple {{BlockSplitBloomFilter}} as 
> candidates and inserts values in the candidates at the same time. Use the 
> largest bloom filter as an approximate deduplication counter, and then remove 
> incapable bloom filter candidates during data insertion.



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