This is an automated email from the ASF dual-hosted git repository. leirui pushed a commit to branch research/LTS-visualization in repository https://gitbox.apache.org/repos/asf/iotdb.git
commit adb5423a6b2b5ce85af15091676b72438d78b6b1 Author: Lei Rui <[email protected]> AuthorDate: Thu Feb 1 00:37:24 2024 +0800 add --- .../groupby/LocalGroupByExecutorTri_ILTS.java | 38 ++++++++++++---------- 1 file changed, 20 insertions(+), 18 deletions(-) diff --git a/server/src/main/java/org/apache/iotdb/db/query/dataset/groupby/LocalGroupByExecutorTri_ILTS.java b/server/src/main/java/org/apache/iotdb/db/query/dataset/groupby/LocalGroupByExecutorTri_ILTS.java index 5e20c45fe9c..195be79bf0a 100644 --- a/server/src/main/java/org/apache/iotdb/db/query/dataset/groupby/LocalGroupByExecutorTri_ILTS.java +++ b/server/src/main/java/org/apache/iotdb/db/query/dataset/groupby/LocalGroupByExecutorTri_ILTS.java @@ -19,13 +19,6 @@ package org.apache.iotdb.db.query.dataset.groupby; -import java.io.IOException; -import java.nio.ByteBuffer; -import java.util.ArrayList; -import java.util.HashMap; -import java.util.List; -import java.util.Map; -import java.util.Set; import org.apache.iotdb.db.conf.IoTDBConfig; import org.apache.iotdb.db.conf.IoTDBDescriptor; import org.apache.iotdb.db.engine.querycontext.QueryDataSource; @@ -49,9 +42,18 @@ import org.apache.iotdb.tsfile.read.filter.GroupByFilter; import org.apache.iotdb.tsfile.read.filter.basic.Filter; import org.apache.iotdb.tsfile.read.reader.page.PageReader; import org.apache.iotdb.tsfile.utils.Pair; + import org.slf4j.Logger; import org.slf4j.LoggerFactory; +import java.io.IOException; +import java.nio.ByteBuffer; +import java.util.ArrayList; +import java.util.HashMap; +import java.util.List; +import java.util.Map; +import java.util.Set; + public class LocalGroupByExecutorTri_ILTS implements GroupByExecutor { private static final IoTDBConfig CONFIG = IoTDBDescriptor.getInstance().getConfig(); @@ -236,7 +238,7 @@ public class LocalGroupByExecutorTri_ILTS implements GroupByExecutor { // TODO 以后元数据可以增加sum of timestamps，目前就基于时间戳均匀间隔1的假设来处理 rt += (chunkSuit4Tri.chunkMetadata.getStartTime() - + chunkSuit4Tri.chunkMetadata.getEndTime()) + + chunkSuit4Tri.chunkMetadata.getEndTime()) * chunkSuit4Tri.chunkMetadata.getStatistics().getCount() / 2.0; rv += chunkSuit4Tri.chunkMetadata.getStatistics().getSumDoubleValue(); @@ -297,18 +299,18 @@ public class LocalGroupByExecutorTri_ILTS implements GroupByExecutor { // 然后遍历如果这个chunk的非紧致上限<=当前已知的maxDistance，那么整个chunk都不用管了 for (ChunkSuit4Tri chunkSuit4Tri : chunkSuit4TriList) { long[] rect_t = - new long[]{ - chunkSuit4Tri.chunkMetadata.getStartTime(), // FPt - chunkSuit4Tri.chunkMetadata.getEndTime(), // LPt - chunkSuit4Tri.chunkMetadata.getStatistics().getBottomTimestamp(), // BPt - chunkSuit4Tri.chunkMetadata.getStatistics().getTopTimestamp() // TPt + new long[] { + chunkSuit4Tri.chunkMetadata.getStartTime(), // FPt + chunkSuit4Tri.chunkMetadata.getEndTime(), // LPt + chunkSuit4Tri.chunkMetadata.getStatistics().getBottomTimestamp(), // BPt + chunkSuit4Tri.chunkMetadata.getStatistics().getTopTimestamp() // TPt }; double[] rect_v = - new double[]{ - (double) chunkSuit4Tri.chunkMetadata.getStatistics().getFirstValue(), // FPv - (double) chunkSuit4Tri.chunkMetadata.getStatistics().getLastValue(), // LPv - (double) chunkSuit4Tri.chunkMetadata.getStatistics().getMinValue(), // BPv - (double) chunkSuit4Tri.chunkMetadata.getStatistics().getMaxValue() // TPv + new double[] { + (double) chunkSuit4Tri.chunkMetadata.getStatistics().getFirstValue(), // FPv + (double) chunkSuit4Tri.chunkMetadata.getStatistics().getLastValue(), // LPv + (double) chunkSuit4Tri.chunkMetadata.getStatistics().getMinValue(), // BPv + (double) chunkSuit4Tri.chunkMetadata.getStatistics().getMaxValue() // TPv }; // 用落在桶内的元数据点（紧致下限）更新maxDistance&select_t&select_v for (int i = 0; i < 4; i++) {
