IntenseFinance/nosqlbench
3
0
Fork 0
mirror of https://github.com/nosqlbench/nosqlbench.git synced 2025-02-25 18:55:28 -06:00
Code Issues Packages Projects Releases Wiki Activity

added support for generating payload for multiple columns of any supported data type

Browse Source
This commit is contained in:
Mark Wolters
2023-12-05 12:18:17 -04:00
parent 60ac4f645e
commit 17b7dbdaa4
2 changed files with 23 additions and 67 deletions
Download Patch File Download Diff File Expand all files Collapse all files

66
virtdata-lib-hdf5/src/main/java/io/nosqlbench/virtdata/library/hdf5/from_long/to_array/HdfDatasetToPayload.java
View File

@@ -1,66 +0,0 @@
/*
* Copyright (c) 2023 nosqlbench
*
* Licensed 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 io.nosqlbench.virtdata.library.hdf5.from_long.to_array;
import io.nosqlbench.virtdata.api.annotations.Categories;
import io.nosqlbench.virtdata.api.annotations.Category;
import io.nosqlbench.virtdata.api.annotations.ThreadSafeMapper;
import io.nosqlbench.virtdata.library.hdf5.from_long.AbstractHdfFileToVectorType;
import java.util.HashMap;
import java.util.Map;
import java.util.function.LongFunction;
@ThreadSafeMapper
@Categories(Category.experimental)
public class HdfDatasetToPayload extends AbstractHdfFileToVectorType implements LongFunction<Object[]> {
private final Map<String,Class> typeMap = new HashMap<>();
public HdfDatasetToPayload(String filename, String datasetName, String columnDS, String columnTypeDS) {
super(filename, datasetName);
populateTypeMap(columnDS, columnTypeDS);
}
private void populateTypeMap(String columnDS, String columnTypeDS) {
Object columnDataset = hdfFile.getDatasetByPath(columnDS).getData();
Object columnTypeDataset = hdfFile.getDatasetByPath(columnTypeDS).getData();
String[] columnNames = (String[]) columnDataset;
String[] columnTypes = (String[]) columnTypeDataset;
if (columnNames.length != columnTypes.length) {
throw new RuntimeException("Left hand dataset and right hand dataset must be the same length");
}
for (int i = 0; i < columnNames.length; i++) {
String columnName = columnNames[i];
String columnType = columnTypes[i];
Class<?> type = switch (columnType) {
case "int" -> int.class;
case "long" -> long.class;
case "float" -> float.class;
case "double" -> double.class;
case "String" -> String.class;
default -> throw new RuntimeException("Unsupported type: " + columnType);
};
typeMap.put(columnName, type);
}
}
@Override
public Object[] apply(long value) {
return new Object[0];
}
}

24
virtdata-lib-hdf5/src/main/java/io/nosqlbench/virtdata/library/hdf5/from_long/to_string/HdfDatasetToStrings.java
View File

@@ -21,6 +21,7 @@ import io.nosqlbench.virtdata.api.annotations.Category;
import io.nosqlbench.virtdata.api.annotations.ThreadSafeMapper;
import io.nosqlbench.virtdata.library.hdf5.from_long.AbstractHdfFileToVectorType;
import java.util.Arrays;
import java.util.function.LongFunction;
/**
@@ -46,7 +47,28 @@ public class HdfDatasetToStrings extends AbstractHdfFileToVectorType implements
sliceDimensions[i] = dims[i];
}
}
return ((String[])dataset.getData(sliceOffset, sliceDimensions))[0];
String payload = null;
switch(dataset.getJavaType().getSimpleName().toLowerCase()) {
case "string" ->
payload = ((String[])dataset.getData(sliceOffset, sliceDimensions))[0];
case "int" ->
payload = Arrays.toString(((int[][]) dataset.getData(sliceOffset, sliceDimensions))[0]);
case "float" ->
payload = Arrays.toString(((float[][]) dataset.getData(sliceOffset, sliceDimensions))[0]);
case "short" ->
payload = Arrays.toString(((short[][]) dataset.getData(sliceOffset, sliceDimensions))[0]);
case "long" ->
payload = Arrays.toString(((long[][]) dataset.getData(sliceOffset, sliceDimensions))[0]);
case "double" ->
payload = Arrays.toString(((double[][]) dataset.getData(sliceOffset, sliceDimensions))[0]);
case "char" ->
payload = String.valueOf(((char[][])dataset.getData(sliceOffset, sliceDimensions))[0]);
}
if (payload == null) {
throw new RuntimeException("Unsupported datatype: " + dataset.getJavaType().getSimpleName());
}
payload = payload.replaceAll("\\[", "").replaceAll("\\]", "");
return payload;
}
}