(I) Experiment of the necessity of TimeseriesMetadata
After we store TimeseriesMetadata together with ChunkMetadata, the necessity of TimeseriesMetadata needs to be reconsidered. We need some experiments for decision.
TimeseriesMetadata for Aggregation query and raw data query under different circumstances for one timeseries in one tsfile.
Each chunk has 100 points. Each query contains 500 TsFiles.
(1) with TimeseriesMetadata: origin TimeseriesMetadata
(2) without TimeseriesMetadata: TimeseriesMetadata has no statistics
And test query for 1 timeseries in TsFile which have 1 timeseries and 1000 timeseries seperately.
Writing:
String path = "/home/fit/szs/data/data/sequence/root.sg/0/" + chunkNum + "/test" + fileIndex + ".tsfile"; File f = FSFactoryProducer.getFSFactory().getFile(path); if (f.exists()) { f.delete(); } try (TsFileWriter tsFileWriter = new TsFileWriter(f)) { // only one timeseries tsFileWriter.registerTimeseries( new Path(Constant.DEVICE_PREFIX, Constant.SENSOR_1), new UnaryMeasurementSchema(Constant.SENSOR_1, TSDataType.INT64, TSEncoding.RLE)); // construct TSRecord for (int i = 1; i <= chunkNum * 100; i++) { TSRecord tsRecord = new TSRecord(i, Constant.DEVICE_PREFIX); DataPoint dPoint1 = new LongDataPoint(Constant.SENSOR_1, i); tsRecord.addTuple(dPoint1); // write TSRecord tsFileWriter.write(tsRecord); if (i % 100 == 0) { tsFileWriter.flushAllChunkGroups(); } } }
Raw data query:
for (int fileIndex = 0; fileIndex < fileNum; fileIndex++) { // file path String path = "/home/fit/szs/data/data/sequence/root.sg/0/" + chunkNum + "/test" + fileIndex + ".tsfile"; // raw data query try (TsFileSequenceReader reader = new TsFileSequenceReader(path); ReadOnlyTsFile readTsFile = new ReadOnlyTsFile(reader)) { ArrayList<Path> paths = new ArrayList<>(); paths.add(new Path(DEVICE1, "sensor_1")); QueryExpression queryExpression = QueryExpression.create(paths, null); long startTime = System.nanoTime(); QueryDataSet queryDataSet = readTsFile.query(queryExpression); while (queryDataSet.hasNext()) { queryDataSet.next(); } costTime += (System.nanoTime() - startTime); } }
Aggregation query:
long totalStartTime = System.nanoTime(); for (int fileIndex = 0; fileIndex < fileNum; fileIndex++) { // file path String path = "/home/fit/szs/data/data/sequence/root.sg/0/" + chunkNum + "/test" + fileIndex + ".tsfile"; // aggregation query try (TsFileSequenceReader reader = new TsFileSequenceReader(path)) { Path seriesPath = new Path(DEVICE1, "sensor_1"); long startTime = System.nanoTime(); TimeseriesMetadata timeseriesMetadata = reader.readTimeseriesMetadata(seriesPath, false); long count = timeseriesMetadata.getStatistics().getCount(); costTime += (System.nanoTime() - startTime); } } System.out.println( "Total raw read cost time: " + (System.nanoTime() - totalStartTime) / 1000_000 + "ms"); System.out.println("Index area cost time: " + costTime / 1000_000 + "ms");
1 timeseries in one tsfile:
chunk number | 1 | 2 | 3 | 5 | 8 | 10 | 15 | 20 | 25 | ||
raw | with timeseriesMetadata | overall cost time (ms) | 210 | 230 | 237 | 250 | 276 | 297 | 309 | 344 | 374 |
index area time (ms) | 116 | 131 | 142 | 156 | 185 | 197 | 220 | 255 | 282 | ||
without timeseriesMetadata | overall cost time (ms) | 219 | 223 | 242 | 267 | 287 | 302 | 334 | 357 | ||
index area time (ms) | 131 | 136 | 155 | 182 | 200 | 219 | 251 | 274 | |||
count(*) | with timeseriesMetadata | overall cost time (ms) | 89 | 90 | 91 | 93 | 93 | 93 | 94 | 97 | 97 |
index area time (ms) | 15 | 16 | 16 | 16 | 16 | 16 | 16 | 17 | 17 | ||
without timeseriesMetadata | overall cost time (ms) | 122 | 123 | 127 | 127 | 127 | 127 | 128 | 130 | ||
index area time (ms) | 50 | 50 | 50 | 50 | 51 | 52 | 52 | 53 |
1000 timeseries in one tsfile: (query for 1 timeseries as well)
chunk number | 1 | 2 | 3 | 5 | 8 | 10 | 15 | 20 | 25 | ||
raw | with timeseriesMetadata | overall cost time (ms) | 421 | 478 | 550 | 673 | 910 | 998 | 1394 | 1637 | 1966 |
index area time (ms) | 274 | 332 | 403 | 528 | 763 | 853 | 1249 | 1496 | 1795 | ||
without timeseriesMetadata | overall cost time (ms) | 489 | 537 | 672 | 903 | 1010 | 1371 | 1650 | 1938 | ||
index area time (ms) | 340 | 393 | 528 | 758 | 864 | 1232 | 1511 | 1789 | |||
count(*) | with timeseriesMetadata | overall cost time (ms) | 260 | 271 | 290 | 331 | 399 | 397 | 562 | 609 | 647 |
index area time (ms) | 133 | 142 | 158 | 197 | 265 | 267 | 427 | 472 | 513 | ||
without timeseriesMetadata | overall cost time (ms) | 307 | 326 | 359 | 428 | 447 | 583 | 620 | 713 | ||
index area time (ms) | 177 | 195 | 227 | 296 | 315 | 447 | 486 | 553 |
Conclusion:
- Although the index area structure with no TimeseriesMetadata speeds up a little in raw data query,
it reduces the speed a lot in aggregation query. => We should reserve TimeseriesMetadata. - The time cost does not change in the data area of TsFile.
(II) Experiment about combine Chunk and Page
Do we need Chunk and Page, or reserve one is ok?
How many points can a chunk have when chunk size = 64K, 1M, 2M, 3M, and 4M?
chunk size | ~64K | ~1M | ~2M | ~3M | ~4M |
points number | 7,977 | 125,000 | 260,000 | 390,000 | 520,000 |
page number | 1 | 16 | 32 | 49 | 66 |
page size (uncompressed) | 65398 | 65398 | 65398 | 65398 | 65398 |
page size (compressed) | 64275 | 64275 | 64275 | 64275 | 64275 |
(III) Experiment about how to store PageHeader