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Posted to reviews@iotdb.apache.org by GitBox <gi...@apache.org> on 2021/02/01 08:51:05 UTC
[GitHub] [iotdb] HTHou commented on a change in pull request #2601: Update tsdb comparison doc
HTHou commented on a change in pull request #2601:
URL: https://github.com/apache/iotdb/pull/2601#discussion_r567646365
##########
File path: docs/UserGuide/Comparison/TSDB-Comparison.md
##########
@@ -284,39 +284,58 @@ It is somehow right. But, if you consider the performance, you may change your m
#### quick review
-Given a workload:
-
* Write:
-10 clients write data concurrently. The number of storage group is 50. There are 1000 devices and each device has 100 measurements (i.e.,, 100K time series totally).
-The data type is float and IoTDB uses RLE encoding and Snappy compression.
-IoTDB uses batch insertion API and the batch size is 100 (write 100 data points per write API call).
+We test write performance from two aspects: *batch size* and *client num*, The number of storage group is 10. There are 1000 devices and each device has 100 measurements(i.e.,, 100K time series totally).
* Read:
-50 clients read data concurrently. Each client just read data from 1 device with 10 measurements in one storage group.
+10 clients read data concurrently. The number of storage group is 10. There are 10 devices and each device has 10 measurements(i.e.,, 100 time series totally).
+The data type is *double*, encoding type is *GORILLA*
-IoTDB is v0.9.0.
+IoTDB is v0.11.1.
Review comment:
```suggestion
The IoTDB version is v0.11.1.
```
##########
File path: docs/UserGuide/Comparison/TSDB-Comparison.md
##########
@@ -284,39 +284,58 @@ It is somehow right. But, if you consider the performance, you may change your m
#### quick review
-Given a workload:
-
* Write:
-10 clients write data concurrently. The number of storage group is 50. There are 1000 devices and each device has 100 measurements (i.e.,, 100K time series totally).
-The data type is float and IoTDB uses RLE encoding and Snappy compression.
-IoTDB uses batch insertion API and the batch size is 100 (write 100 data points per write API call).
+We test write performance from two aspects: *batch size* and *client num*, The number of storage group is 10. There are 1000 devices and each device has 100 measurements(i.e.,, 100K time series totally).
* Read:
-50 clients read data concurrently. Each client just read data from 1 device with 10 measurements in one storage group.
+10 clients read data concurrently. The number of storage group is 10. There are 10 devices and each device has 10 measurements(i.e.,, 100 time series totally).
Review comment:
```suggestion
10 clients read data concurrently. The number of storage group is 10. There are 10 devices and each device has 10 measurements (i.e.,, 100 time series total).
```
##########
File path: docs/UserGuide/Comparison/TSDB-Comparison.md
##########
@@ -284,39 +284,58 @@ It is somehow right. But, if you consider the performance, you may change your m
#### quick review
-Given a workload:
-
* Write:
-10 clients write data concurrently. The number of storage group is 50. There are 1000 devices and each device has 100 measurements (i.e.,, 100K time series totally).
-The data type is float and IoTDB uses RLE encoding and Snappy compression.
-IoTDB uses batch insertion API and the batch size is 100 (write 100 data points per write API call).
+We test write performance from two aspects: *batch size* and *client num*, The number of storage group is 10. There are 1000 devices and each device has 100 measurements(i.e.,, 100K time series totally).
Review comment:
```suggestion
We test the performance of writing from two aspects: *batch size* and *client num*. The number of storage group is 10. There are 1000 devices and each device has 100 measurements(i.e.,, 100K time series total).
```
##########
File path: docs/UserGuide/Comparison/TSDB-Comparison.md
##########
@@ -284,39 +284,58 @@ It is somehow right. But, if you consider the performance, you may change your m
#### quick review
-Given a workload:
-
* Write:
-10 clients write data concurrently. The number of storage group is 50. There are 1000 devices and each device has 100 measurements (i.e.,, 100K time series totally).
-The data type is float and IoTDB uses RLE encoding and Snappy compression.
-IoTDB uses batch insertion API and the batch size is 100 (write 100 data points per write API call).
+We test write performance from two aspects: *batch size* and *client num*, The number of storage group is 10. There are 1000 devices and each device has 100 measurements(i.e.,, 100K time series totally).
* Read:
-50 clients read data concurrently. Each client just read data from 1 device with 10 measurements in one storage group.
+10 clients read data concurrently. The number of storage group is 10. There are 10 devices and each device has 10 measurements(i.e.,, 100 time series totally).
+The data type is *double*, encoding type is *GORILLA*
-IoTDB is v0.9.0.
+IoTDB is v0.11.1.
**Write performance**:
-We write 112GB data totally.
+* batch size:
+
+10 clients write data concurrently.
+IoTDB uses batch insertion API and the batch size is distributed from 1(1ms) to 6000(1min) (write N data points per write API call).
Review comment:
```suggestion
IoTDB uses batch insertion API and the batch size is distributed from 1ms to 1min (write N data points per write API call).
```
##########
File path: docs/UserGuide/Comparison/TSDB-Comparison.md
##########
@@ -327,58 +346,29 @@ We provide a benchmarking tool, called IoTDB-benchamrk (https://github.com/thula
it supports IoTDB, InfluxDB, KairosDB, TimescaleDB, OpenTSDB. We have a [article](https://arxiv.org/abs/1901.08304) for comparing these systems using the benchmark tool.
When we publish the article, IoTDB just entered Apache incubator, so we deleted the performance of IoTDB in that article. But after comparison, some results are presented here.
-- **IoTDB: 0.8.0**. (notice: **IoTDB v0.9 outperforms than v0.8**, the result will be updated once experiments on v0.9 are finished)
-- InfluxDB: 1.5.1.
-- OpenTSDB: 2.3.1 (HBase 1.2.8)
-- KairosDB: 1.2.1 (Cassandra 3.11.3)
-- TimescaleDB: 1.0.0 (PostgreSQL 10.5)
-
All TSDB run on the same server one by one.
- For InfluxDB, we set the cache-max-memory-size and max-series-perbase as unlimited (otherwise it will be timeout quickly)
Review comment:
```suggestion
- For InfluxDB, we set the cache-max-memory-size and max-series-perbase as unlimited (otherwise it will be timeout quickly).
```
##########
File path: docs/UserGuide/Comparison/TSDB-Comparison.md
##########
@@ -327,58 +346,29 @@ We provide a benchmarking tool, called IoTDB-benchamrk (https://github.com/thula
it supports IoTDB, InfluxDB, KairosDB, TimescaleDB, OpenTSDB. We have a [article](https://arxiv.org/abs/1901.08304) for comparing these systems using the benchmark tool.
Review comment:
```suggestion
it supports IoTDB, InfluxDB, KairosDB, TimescaleDB, OpenTSDB. We have an [article](https://arxiv.org/abs/1901.08304) for comparing these systems using the benchmark tool.
```
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