Error Handling Spring JdbcTemplate batchUpdate - spring

I am trying to update thousands of rows in a table using batchUpdate. My requirements are:
1) Assume there are 1000 records in a batch. Record No 235 caused an error. How do I find out which record caused the error.
2) Assume that record 600 did not result in an update (reason could be no record matching the where clause). How can I find out records that did not result in an update.
3) In both scenarios above how can I continue processing the remaining records.

The only solution after long search and debug is to go to BatchUpdateException class and find the negative element and deduce the value of the insertion that is in error from the MAP.
import java.sql.BatchUpdateException;
import java.sql.PreparedStatement;
import java.sql.SQLException;
import java.sql.Statement;
import java.util.List;
import java.util.Map;
import org.springframework.jdbc.core.BatchPreparedStatementSetter;
import org.springframework.stereotype.Repository;
import org.springframework.transaction.annotation.Propagation;
import org.springframework.transaction.annotation.Transactional;
#Transactional(propagation = Propagation.REQUIRED, rollbackFor = Exception.class)
#Repository("dao_")
public class YouDao extends CommunDao implements IyouDao {
public void bulkInsert(final List<Map<String, String>> map)
throws BusinessException {
try {
String sql = " insert into your_table " + "( aa,bb )"
+ "values " + "( ?,? )";
BatchPreparedStatementSetter batchPreparedStatementSetter = new BatchPreparedStatementSetter() {
#Override
public void setValues(PreparedStatement ps, int i)
throws SQLException {
Map<String, String> bean = map.get(i);
ps.setString(1, bean.get("aa"));
ps.setString(2, bean.get("bb"));
//..
//..
}
#Override
public int getBatchSize() {
return map.size();
}
};
getJdbcTemplate().batchUpdate(sql, batchPreparedStatementSetter);
}
catch (Exception e) {
if (e.getCause() instanceof BatchUpdateException) {
BatchUpdateException be = (BatchUpdateException) e.getCause();
int[] batchRes = be.getUpdateCounts();
if (batchRes != null && batchRes.length > 0) {
for (int index = 0; index < batchRes.length; index++) {
if (batchRes[index] == Statement.EXECUTE_FAILED) {
logger.error("Error execution >>>>>>>>>>>"
+ index + " --- , codeFail : " + batchRes[index]
+ "---, line " + map.get(index));
}
}
}
}
throw new BusinessException(e);
}
}
}

int[] rows =jdbcTemplate.batchUpdate(TbCareQueryConstant.SQL_UPDATE_BANKDETAILS_OF_USER, new BatchPreparedStatementSetter(){
.....
your code
}
for(int i=0 ; i < rows.length ; i++){
if(rows[i] == 0){
}
}

Related

How to implement a worker thread that will process Kinesis records and update GUI in javaFx?

I'm working on a micro-services monitoring app.
My app supposes to update a GUI accordingly when receiving a new consumed
record, meaning:
When I receive a new record:
1)I check if the request it represents is a part of a legal flow, and
if that flow already has representation in the GUI.
By representation, I mean a set of circles that represent the full flow.
For example, if I get a transaction (MS1 received request) a legal flow num 1: that is MS1 to MS2 to MS3, so my GUI will add a table column with 2 grey circles: MS1 to MS2 and MS2 to MS3. Next, when a record: MS2 received from
MS1 is consumed I will paint the first circle green and so on.
My problem is:
I don't understand how to "tap into" Amazon's KCL code (presented here).
meaning, I don't know how to make that a consumed record will trigger event in my JavaFX GUI that will update the GUI accordingly.
Help would be much appreciated!
package com.kinesisdataconsumer;
import java.io.UnsupportedEncodingException;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
import java.util.concurrent.Executors;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicLong;
import com.DATA_STATUS;
import com.DataBase;
import com.MonitoringLogicImpl;
import com.kinesisdataproducer.Producer;
import com.Transaction;
import org.json.JSONObject;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import com.amazonaws.auth.DefaultAWSCredentialsProviderChain;
import com.amazonaws.services.kinesis.clientlibrary.interfaces.IRecordProcessor;
import com.amazonaws.services.kinesis.clientlibrary.interfaces.IRecordProcessorCheckpointer;
import com.amazonaws.services.kinesis.clientlibrary.interfaces.IRecordProcessorFactory;
import com.amazonaws.services.kinesis.clientlibrary.lib.worker.InitialPositionInStream;
import com.amazonaws.services.kinesis.clientlibrary.lib.worker.KinesisClientLibConfiguration;
import com.amazonaws.services.kinesis.clientlibrary.lib.worker.Worker;
import com.amazonaws.services.kinesis.clientlibrary.lib.worker.ShutdownReason;
import com.amazonaws.services.kinesis.model.Record;
public class Consumer implements IRecordProcessorFactory {
private static final Logger log = LoggerFactory.getLogger(Consumer.class);
public DataBase dataBase;
public ArrayList<Transaction> transactionList;
public MonitoringLogicImpl monitoringLogic;
private final AtomicLong largestTimestamp = new AtomicLong(0);
private final List<Long> sequenceNumbers = new ArrayList<>();
private final Object lock = new Object();
public Consumer(DataBase database, ArrayList<Transaction> transactions, MonitoringLogicImpl monitoringLogicImplementation){
dataBase = database;
transactionList = transactions;
monitoringLogic = monitoringLogicImplementation;
}
private class RecordProcessor implements IRecordProcessor {
#Override
public void initialize(String shardId) {}
#Override
public void processRecords(List<Record> records, IRecordProcessorCheckpointer checkpointer) {
long timestamp = 0;
List<Long> seqNos = new ArrayList<>();
for (Record r : records) {
timestamp = Math.max(timestamp, Long.parseLong(r.getPartitionKey()));
try {
byte[] b = new byte[r.getData().remaining()];
r.getData().get(b);
seqNos.add(Long.parseLong(new String(b, "UTF-8").split("#")[0]));
//this thread adds the transaction to the DB
Thread addTransactionToDBThread = new Thread() {
public void run() {
try {
JSONObject jsonObj = new JSONObject(new String(b, "UTF-8").split("#")[1]);
Transaction transaction = Transaction.convertJsonToTransaction(jsonObj);
//add the transaction to the database
dataBase.addTransactionToDB(transaction);
//update the user-interface about the last transaction in the system
DATA_STATUS transactionStatus = monitoringLogic.getStatus(transaction);
monitoringLogic.updateUI(transaction.getUuid(), transaction.getSender(), transaction.getReceiver(), transactionStatus);
Thread.sleep(1000);
} catch(InterruptedException e) {
e.printStackTrace();
} catch (UnsupportedEncodingException e) {
e.printStackTrace();
}
}
};
addTransactionToDBThread.start();
} catch (Exception e) {
log.error("Error parsing record", e);
System.exit(1);
}
}
synchronized (lock) {
if (largestTimestamp.get() < timestamp) {
log.info(String.format(
"Found new larger timestamp: %d (was %d), clearing state",
timestamp, largestTimestamp.get()));
largestTimestamp.set(timestamp);
sequenceNumbers.clear();
}
// Only add to the shared list if our data is from the latest run.
if (largestTimestamp.get() == timestamp) {
sequenceNumbers.addAll(seqNos);
Collections.sort(sequenceNumbers);
}
}
try {
checkpointer.checkpoint();
} catch (Exception e) {
log.error("Error while trying to checkpoint during ProcessRecords", e);
}
}
#Override
public void shutdown(IRecordProcessorCheckpointer checkpointer, ShutdownReason reason) {
log.info("Shutting down, reason: " + reason);
try {
checkpointer.checkpoint();
} catch (Exception e) {
log.error("Error while trying to checkpoint during Shutdown", e);
}
}
}
/**
* Log a message indicating the current state.
*/
public void logResults() {
synchronized (lock) {
if (largestTimestamp.get() == 0) {
return;
}
if (sequenceNumbers.size() == 0) {
log.info("No sequence numbers found for current run.");
return;
}
// The producer assigns sequence numbers starting from 1, so we
// start counting from one before that, i.e. 0.
long last = 0;
long gaps = 0;
for (long sn : sequenceNumbers) {
if (sn - last > 1) {
gaps++;
}
last = sn;
}
log.info(String.format(
"Found %d gaps in the sequence numbers. Lowest seen so far is %d, highest is %d",
gaps, sequenceNumbers.get(0), sequenceNumbers.get(sequenceNumbers.size() - 1)));
}
}
#Override
public IRecordProcessor createProcessor() {
return this.new RecordProcessor();
}
public void consumeData() {
KinesisClientLibConfiguration config =
new KinesisClientLibConfiguration(
"KinesisProducerLibSampleConsumer",
Producer.STREAM_NAME,
new DefaultAWSCredentialsProviderChain(),
"KinesisProducerLibSampleConsumer")
.withRegionName(Producer.REGION)
.withInitialPositionInStream(InitialPositionInStream.LATEST);
final Consumer consumer = new Consumer(dataBase, transactionList, monitoringLogic);
Executors.newScheduledThreadPool(1).scheduleAtFixedRate(new Runnable() {
#Override
public void run() {
consumer.logResults();
}
}, 10, 1, TimeUnit.SECONDS);
new Worker.Builder()
.recordProcessorFactory(consumer)
.config(config)
.build()
.run();
}
}

Find count of rows with empty value in Hbase

I have populated a Hbase table with rowid and vrious information pertaining to tweet such as clean-text,url,hashtag etc. as follows
902221655086211073 column=clean-tweet:clean-text-cta, timestamp=1514793745304, value=democrat mayor order hurricane harvey stand houston
However while populating I noticed that the some of the rows are empty like
902487280543305728 column=clean-tweet:clean-text-cta, timestamp=1514622371008, value=
Now how do I find the count of rows that are having data?
Please help me in this
There is no provision to do this in HBase shell as of now. May be you can use a simple code like this to get a number of records with no value for the provided column qualifier.
CountAndFilter [tableName] [columnFamily] [columnQualifier]
import java.io.IOException;
import org.apache.hadoop.hbase.HBaseConfiguration;
import org.apache.hadoop.hbase.TableName;
import org.apache.hadoop.hbase.client.Admin;
import org.apache.hadoop.hbase.client.Connection;
import org.apache.hadoop.hbase.client.ConnectionFactory;
import org.apache.hadoop.hbase.client.Result;
import org.apache.hadoop.hbase.client.ResultScanner;
import org.apache.hadoop.hbase.client.Scan;
import org.apache.hadoop.hbase.client.Table;
import org.apache.hadoop.hbase.util.Bytes;
public class CountAndFilter {
private static Connection conn;
private static int recordsWithoutValue = 0;
public static Admin getConnection() throws IOException {
if (conn == null) {
conn = ConnectionFactory.createConnection(HBaseConfiguration.create());
}
return conn.getAdmin();
}
public static void main(String args[]) throws IOException {
getConnection();
scan(args[0], args[1], args[2]);
System.out.println("Records with empty value : " + recordsWithoutValue);
}
public static void scan(String tableName, String columnFamily, String columnQualifier) throws IOException {
Table table = conn.getTable(TableName.valueOf(tableName));
ResultScanner rs = table.getScanner(new Scan().addColumn(Bytes.toBytes(columnFamily), Bytes.toBytes(columnQualifier)));
Result res = null;
try {
while ((res = rs.next()) != null) {
if (res.containsEmptyColumn(Bytes.toBytes(columnFamily), Bytes.toBytes(columnQualifier))){
recordsWithoutValue++;
}
}
} finally {
rs.close();
}
}
}

Confluent Kafka Avro deserializer for spring boot kafka listener

Does somebody implemented confluent-kafka messages deserializer to consume kafka messages by spring "#KafkaListener"-s ?
Here is my answer, which I've implemented based on: "io.confluent.kafka.serializers.AbstractKafkaAvroDeserializer"
import java.io.IOException;
import java.nio.ByteBuffer;
import java.util.Arrays;
import java.util.Map;
import javax.xml.bind.DatatypeConverter;
import org.apache.avro.Schema;
import org.apache.avro.io.DatumReader;
import org.apache.avro.io.DecoderFactory;
import org.apache.avro.specific.SpecificDatumReader;
import org.apache.avro.specific.SpecificRecordBase;
import org.apache.kafka.common.errors.SerializationException;
import org.apache.kafka.common.serialization.Deserializer;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
public class AvroConfluentDeserializer<T extends SpecificRecordBase> implements Deserializer<T> {
private static final Logger LOG = LoggerFactory.getLogger(AvroConfluentDeserializer.class);
protected static final byte MAGIC_BYTE = 0x0;
protected static final int idSize = 4;
private final DecoderFactory decoderFactory = DecoderFactory.get();
protected final Class<T> targetType;
public AvroConfluentDeserializer(Class<T> targetType) {
this.targetType = targetType;
}
#Override
public void close() {
// No-op
}
#Override
public void configure(Map<String, ?> arg0, boolean arg1) {
// No-op
}
#Override
public T deserialize(String topic, byte[] data) {
try {
T result = null;
if (data != null) {
LOG.info("data='{}'", DatatypeConverter.printHexBinary(data));
result = (T) deserializePayload(data, targetType.newInstance().getSchema());
LOG.info("deserialized data='{}'", result);
}
return result;
} catch (Exception ex) {
throw new SerializationException(
"Can't deserialize data '" + Arrays.toString(data) + "' from topic '" + topic + "'", ex);
}
}
protected T deserializePayload(byte[] payload, Schema schema) throws SerializationException {
int id = -1;
try {
ByteBuffer buffer = getByteBuffer(payload);
id = buffer.getInt();
int length = buffer.limit() - 1 - idSize;
int start = buffer.position() + buffer.arrayOffset();
DatumReader<T> reader = new SpecificDatumReader<T>(schema);
return reader.read(null, decoderFactory.binaryDecoder(buffer.array(), start, length, null));
} catch (IOException | RuntimeException e) {
throw new SerializationException("Error deserializing Avro message for id " + id, e);
}
}
private ByteBuffer getByteBuffer(byte[] payload) {
ByteBuffer buffer = ByteBuffer.wrap(payload);
if (buffer.get() != MAGIC_BYTE) {
throw new SerializationException("Unknown magic byte!");
}
return buffer;
}
}

I want to show max,min and avg temperature using hadoop

My project is to show max,min and avg temperature. I have already done it, but I have to show this functions using group by key. There are 4 radio buttons for Year, month, date and city in my application. If I select one then it will ask me to input the aggregate functions(max,min,avg). For these I need to change my CompositeGroupKey class, but I don't have any idea about that. So please help me, and provide inputs about the changes need to be done with the code.
The driver :
import org.apache.hadoop.io.*;
import org.apache.hadoop.fs.*;
import org.apache.hadoop.mapreduce.*;
import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;
import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;
public class MaxTemperature
{
public static void Main (String[] args) throws Exception
{
if (args.length != 2)
{
System.err.println("Please Enter the input and output parameters");
System.exit(-1);
}
Job job = new Job();
job.setJarByClass(MaxTemperature.class);
job.setJobName("Max temperature");
FileInputFormat.addInputPath(job,new Path(args[0]));
FileOutputFormat.setOutputPath(job,new Path (args[1]));
job.setMapperClass(MaxTemperatureMapper.class);
job.setReducerClass(MaxTemperatureReducer.class);
job.setMapOutputKeyClass(CompositeGroupKey.class);
job.setMapOutputValueClass(IntWritable.class);
job.setOutputKeyClass(CompositeGroupKey.class);
job.setOutputValueClass(DoubleWritable.class);
System.exit(job.waitForCompletion(true)?0:1);
}
}
The mapper :
import org.apache.hadoop.io.*;
import org.apache.hadoop.mapreduce.*;
import java.io.IOException;
public class MaxTemperatureMapper extends Mapper <LongWritable, Text, CompositeGroupKey, IntWritable>
{
public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException
{
String line = value.toString();
int year = Integer.parseInt(line.substring(0,4));
String mnth = line.substring(7,10);
int date = Integer.parseInt(line.substring(10,12));
int temp= Integer.parseInt(line.substring(12,14));
CompositeGroupKey cntry = new CompositeGroupKey(year,mnth, date);
context.write(cntry, new IntWritable(temp));
}
}
The reducer :
import org.apache.hadoop.io.DoubleWritable;
import org.apache.hadoop.io.IntWritable;
import org.apache.hadoop.mapreduce.*;
import java.io.IOException;
public class MaxTemperatureReducer extends Reducer <CompositeGroupKey, IntWritable, CompositeGroupKey, CompositeGroupkeyall >{
public void reduce(CompositeGroupKey key, Iterable<IntWritable> values , Context context) throws IOException,InterruptedException
{
Double max = Double.MIN_VALUE;
Double min =Double.MAX_VALUE;
for (IntWritable value : values )
{
min = Math.min(min, value.get());
max = Math.max(max, value.get());
}
CompositeGroupkeyall val =new CompositeGroupkeyall(max,min);
context.write(key, val);
}
}
And the composite key :
import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import org.apache.hadoop.io.WritableComparable;
import org.apache.hadoop.io.WritableUtils;
class CompositeGroupKey implements WritableComparable<CompositeGroupKey> {
int year;
String mnth;
int date;
CompositeGroupKey(int y, String c, int d){
year = y;
mnth = c;
date = d;
}
CompositeGroupKey(){}
public void write(DataOutput out) throws IOException {
out.writeInt(year);
WritableUtils.writeString(out, mnth);
out.writeInt(date);
}
public void readFields(DataInput in) throws IOException {
this.year = in.readInt();
this.mnth = WritableUtils.readString(in);
this.date = in.readInt();
}
public int compareTo(CompositeGroupKey pop) {
if (pop == null)
return 0;
int intcnt;
intcnt = Integer.valueOf(year).toString().compareTo(Integer.valueOf(pop.year).toString());
if(intcnt != 0){
return intcnt;
}else if(mnth.compareTo(pop.mnth) != 0){
return mnth.compareTo(pop.mnth);
}else{
return Integer.valueOf(date).toString().compareTo(Integer.valueOf(pop.date).toString());
}
}
public String toString() {
return year + " :" + mnth.toString() + " :" + date;
}
}
import java.io.DataInput;
import java.io.DataOutput;
import java.io.IOException;
import org.apache.hadoop.io.WritableComparable;
class CompositeGroupkeyall implements WritableComparable<CompositeGroupkeyall> {
Double max;
Double min;
CompositeGroupkeyall(double x, double y){
max = x ;
min = y ;
}
CompositeGroupkeyall(){}
public void readFields(DataInput in) throws IOException {
this.max = in.readDouble();
this.min = in.readDouble();
}
public void write(DataOutput out) throws IOException {
out.writeDouble(max);
out.writeDouble(min);
}
public int compareTo(CompositeGroupkeyall arg0) {
return -1;
}
public String toString() {
return max + " " + min +" " ;
}
}
You can create more key value pairs as below and let the same reducer process the data, all the date/month/year will be processed by the same reducer
CompositeGroupKey cntry = new CompositeGroupKey(year, mnth, date);
CompositeGroupKey cntry_date = new CompositeGroupKey((int)0, "ALL", date);
CompositeGroupKey cntry_mnth = new CompositeGroupKey((int)0, mnth, (int) 1);
CompositeGroupKey cntry_year = new CompositeGroupKey(year, "ALL", (int) 1);
context.write(cntry, new IntWritable(temp));
context.write(cntry_date, new IntWritable(temp));
context.write(cntry_mnth, new IntWritable(temp));
context.write(cntry_year, new IntWritable(temp));

hbase co-processor failing to load from shell

I am trying to add a coprocessor with one hbase table and it is failing with error -
2016-03-15 14:40:14,130 INFO org.apache.hadoop.hbase.regionserver.RSRpcServices: Open PRODUCT_DETAILS,,1457953190424.f687dd250bfd1f18ffbb8075fd625145.
2016-03-15 14:40:14,173 ERROR org.apache.hadoop.hbase.regionserver.RegionCoprocessorHost: Failed to load coprocessor com.optymyze.coprocessors.ProductObserver
java.io.IOException: Failed on local exception: com.google.protobuf.InvalidProtocolBufferException: Protocol message end-group tag did not match expected tag.; Host Details : local host is: "mylocalhost/mylocalhostip"; destination host is: "mydestinationhost":9000;
at org.apache.hadoop.net.NetUtils.wrapException(NetUtils.java:772)
to add co processor I did following -
hbase> disable 'PRODUCT_DETAILS'
hbase> alter 'PRODUCT_DETAILS', METHOD => 'table_att', 'coprocessor'=>'hdfs://mydestinationhost:9000/hbase-coprocessors-0.0.3-SNAPSHOT.jar|com.optymyze.coprocessors.ProductObserver|1001|arg1=1,arg2=2'
now enable 'PRODUCT_DETAILS' won't work.
co processor code is as follows-
package com.optymyze.coprocessors;
import org.apache.hadoop.hbase.KeyValue;
import org.apache.hadoop.hbase.client.HTableInterface;
import org.apache.hadoop.hbase.client.Put;
import org.apache.hadoop.hbase.coprocessor.BaseRegionObserver;
import org.apache.hadoop.hbase.coprocessor.ObserverContext;
import org.apache.hadoop.hbase.coprocessor.RegionCoprocessorEnvironment;
import org.apache.hadoop.hbase.regionserver.wal.WALEdit;
import org.apache.hadoop.hbase.util.Bytes;
import org.slf4j.Logger;
import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import static org.slf4j.LoggerFactory.*;
/**
*
* Created by adnan on 14-03-2016.
*/
public class ProductObserver extends BaseRegionObserver {
private static final Logger LOGGER = getLogger(ProductObserver.class);
private static final String PRODUCT_DETAILS_TABLE = "PRODUCT_DETAILS";
public static final String COLUMN_FAMILY = "CF";
#Override
public void postPut(ObserverContext<RegionCoprocessorEnvironment> e, Put put, WALEdit edit, boolean writeToWAL) throws IOException {
List<KeyValue> kvs = put.getFamilyMap().get(Bytes.toBytes(COLUMN_FAMILY));
LOGGER.info("key values {}", kvs);
Map<String, Integer> qualifierVsValue = getMapForQualifierVsValuesForRequiredOnes(kvs);
LOGGER.info("qualifier values {}", qualifierVsValue);
List<Put> puts = createPuts(kvs, qualifierVsValue);
LOGGER.info("puts values {}", puts);
updateProductTable(e, puts);
LOGGER.info("puts done");
}
private void updateProductTable(ObserverContext<RegionCoprocessorEnvironment> e, List<Put> puts) throws IOException {
HTableInterface productTable = e.getEnvironment().getTable(Bytes.toBytes(PRODUCT_DETAILS_TABLE));
try {
productTable.put(puts);
}finally {
productTable.close();
}
}
private List<Put> createPuts(List<KeyValue> kvs, Map<String, Integer> qualifierVsValue) {
int salePrice, baseline = 0, finalPrice = 0;
List<Put> puts = new ArrayList<Put>(kvs.size());
for (KeyValue kv : kvs) {
if (kv.matchingQualifier(Bytes.toBytes("BASELINE"))) {
baseline = convertToZeroIfNull(qualifierVsValue, "PRICE")
- convertToZeroIfNull(qualifierVsValue, "PRICE")
* convertToZeroIfNull(qualifierVsValue, "DISCOUNT") / 100;
puts.add(newPut(kv, baseline));
}
if (kv.matchingQualifier(Bytes.toBytes("FINALPRICE"))) {
finalPrice = baseline + baseline * convertToZeroIfNull(qualifierVsValue, "UPLIFT") / 100;
puts.add(newPut(kv, finalPrice));
}
if (kv.matchingQualifier(Bytes.toBytes("SALEPRICE"))) {
salePrice = finalPrice * convertToZeroIfNull(qualifierVsValue, "VOLUME");
puts.add(newPut(kv, salePrice));
}
}
return puts;
}
private Map<String, Integer> getMapForQualifierVsValuesForRequiredOnes(List<KeyValue> kvs) {
Map<String, Integer> qualifierVsValue = new HashMap<String, Integer>();
for (KeyValue kv : kvs) {
getValueFromQualifier(kv, "PRICE", qualifierVsValue);
getValueFromQualifier(kv, "DISCOUNT", qualifierVsValue);
getValueFromQualifier(kv, "UPLIFT", qualifierVsValue);
getValueFromQualifier(kv, "VOLUME", qualifierVsValue);
}
return qualifierVsValue;
}
private Integer convertToZeroIfNull(Map<String, Integer> qualifierVsValue, String qualifier) {
Integer v = qualifierVsValue.get(qualifier);
return v == null ? 0 : v;
}
private void getValueFromQualifier(KeyValue kv, String qualifier, Map<String, Integer> qualifierVsValue) {
if (kv.matchingQualifier(Bytes.toBytes(qualifier))) {
qualifierVsValue.put(qualifier, Bytes.toInt(convertToByteZeroIfNull(kv)));
}
}
private Put newPut(KeyValue kv, int newVal) {
Put put = new Put(kv.getValue(), kv.getTimestamp());
put.add(kv.getFamily(), kv.getQualifier(), Bytes.toBytes(newVal));
return put;
}
private byte[] convertToByteZeroIfNull(KeyValue kv) {
return kv.getValue() == null ? Bytes.toBytes(0) : kv.getValue();
}
}

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