Haining Yang

50 papers Journal 38Unranked 12
YearRankTypeTitle / Venue / Authors
2026 J jnl
IEEE Trans. Dependable Secur. Comput.
Axin Wu, Dengguo Feng, Min Zhang, Haining Yang, Jialin Chi
2025 J jnl
IEEE Trans. Veh. Technol.
Shijia Yi, Haining Yang, Yutong Tian, Na Li, Tingjun Li, Yujian Cheng
2025 J jnl
J. Comput. Inf. Technol.
Lei Han, Xuedong Gao, Haining Yang
2025 J jnl
IEEE Wirel. Commun. Lett.
Yutong Tian, Haining Yang, Shijia Yi, Tingjun Li, Zhihang Qu, Na Li, Yujian Cheng
2025 J jnl
IEEE Trans. Computers
Haining Yang, Dengguo Feng, Jing Qin
2025 J jnl
Int. J. Intell. Syst.
Zhongkai Wei, Ye Su, Xi Zhang, Haining Yang, Jing Qin, Jixin Ma
2025 J jnl
IEEE Internet Things J.
Zhongkai Wei, Bo Zhao, Haining Yang, Jing Qin, Jixin Ma
2025 J jnl
IEEE Trans. Inf. Forensics Secur.
Fucai Luo, Xingfu Yan, Haining Yang, Xiaofan Zheng
2025 J jnl
IEEE Trans. Mob. Comput.
Haining Yang, Jinlu Liu, Pingyuan Zhang, Jing Qin, Huaxiong Wang
2025 J jnl
IEEE Trans. Parallel Distributed Syst.
Haining Yang, Dengguo Feng, Jing Qin
2025 conf
OFC
Ruixue Guo, Xun Yu, Haining Yang
2024 J jnl
IEEE Trans. Geosci. Remote. Sens.
Yutong Tian, Haining Yang, Shijia Yi, Tingjun Li, Na Li, Qing Huo Liu
2024 J jnl
J. Opt. Commun. Netw.
Haoyu Wei, Weixin Chen, Haining Yang
2024 J jnl
IEEE Trans. Aerosp. Electron. Syst.
Shijia Yi, Haining Yang, Aya Li, Na Li, Tingjun Li, Zhihang Qu, Yujian Cheng
2023 J jnl
Theor. Comput. Sci.
Pingyuan Zhang, Haining Yang, Liang Zhu, Yanhua Zhang, Hao Wang, Qiuliang Xu
2023 J jnl
IEEE Trans. Dependable Secur. Comput.
Haining Yang, Dengguo Feng, Jing Qin
2023 J jnl
Theor. Comput. Sci.
Yongcheng Song, Jiang Zhang, Xinyi Huang, Wei Wu, Haining Yang
2022 J jnl
Remote. Sens.
Haining Yang, Yuting Liu, Tingjun Li, Shijia Yi, Na Li
2022 J jnl
Int. J. Comput. Commun. Control
Haining Yang, Xuedong Gao, Lei Han, Wei Cui
2022 J jnl
Remote. Sens.
Jun Duan, Min Qin, Wu Fang, Zhitang Liao, Huaqiao Gui, Zheng Shi, Haining Yang, Fanhao Meng, Dou Shao, Jiaqi Hu, Baobin Han, Pinhua Xie, Wenqing Liu
2022 J jnl
IEEE Trans. Geosci. Remote. Sens.
Shijia Yi, Haining Yang, Na Li, Tingjun Li, Yong Fan, Qing Huo Liu
2022 J jnl
IEEE Trans. Dependable Secur. Comput.
Haining Yang, Ye Su, Jing Qin, Huaxiong Wang
2021 conf
OFC
Jiewen Nie, Lei Tian, Song Yue, Zichen Zhang, Haining Yang
2021 J jnl
IEEE Trans. Veh. Technol.
Songlin Li, Shisheng Guo, Jiahui Chen, Xiaqing Yang, Shihao Fan, Chao Jia, Guolong Cui, Haining Yang
2021 J jnl
Int. J. Intell. Syst.
Xi Zhang, Bo Zhao, Jing Qin, Wei Hou, Ye Su, Haining Yang
2021 conf
CNIOT
Haining Yang, Yifei Hao, Tingjun Li, Kai Yu, Na Li
2021 conf
CNIOT
Haining Yang, Meili She, Tingjun Li, Kai Yu, Na Li
2021 conf
CNIOT
Tingjun Li, Wang Yan, Haining Yang, Kai Yu, Na Li
2020 conf
OFC
Peter Wilkinson, Brian Robertson, Sam Giltrap, Oliver Snowdon, Harry Prudden, Haining Yang, Daping Chu
2020 conf
ML4CS (1)
Haining Yang, Ye Su, Jing Qin, Jinhua Ma, Huaxiong Wang
2020 J jnl
Inf. Sci.
Haining Yang, Ye Su, Jing Qin, Huaxiong Wang, Yongcheng Song
2019 J jnl
Signal Process.
Na Li, Haining Yang, Guolong Cui, Lingjiang Kong, Qing Huo Liu
2019 J jnl
Concurr. Comput. Pract. Exp.
Haining Yang, Jiameng Sun, Jing Qin, Jixin Ma
2019 J jnl
IEEE Trans. Geosci. Remote. Sens.
Na Li, Haining Yang, Tingjun Li, Yong Fan, Qing Huo Liu
2019 J jnl
Int. J. Digit. Crime Forensics
Dawei Xie, Haining Yang, Jing Qin, Jixin Ma
2018 conf
OFC
Haining Yang, Philip Dolan, Brian Robertson, Peter Wilkinson, Daping Chu
2018 conf
OFC
Haining Yang, Paul Wright, Brian Robertson, Peter Wilkinson, P. R. Dolan, Andrew Lord, Daping Chu
2018 J jnl
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens.
Haining Yang, Na Li, Tingjun Li, Qing Huo Liu
2017 J jnl
Circuits Syst. Signal Process.
Yun Zhou, Haining Yang, Na Li, Guolong Cui, Lingjiang Kong
2017 conf
OFC
Haining Yang, Rui Wang, Paul Wright, Abhijit Mitra, Brian Robertson, Peter Wilkinson, Subrat Kar, Andrew Lord, Daping Chu
2017 J jnl
JOCN
Haining Yang, Brian Robertson, Peter Wilkinson, Daping Chu
2016 J jnl
IEEE Trans. Geosci. Remote. Sens.
Haining Yang, Tingjun Li, Na Li, Zhiming He, Qing Huo Liu
2016 J jnl
IEEE Trans. Geosci. Remote. Sens.
Haining Yang, Tingjun Li, Na Li, Zhiming He, Qing Huo Liu
2015 J jnl
Signal Process.
Na Li, Guolong Cui, Haining Yang, Lingjiang Kong, Qing Huo Liu, Salvatore Iommelli
2015 J jnl
IEEE Trans. Geosci. Remote. Sens.
Haining Yang, Tingjun Li, Na Li, Zhiming He, Qing Huo Liu
2015 J jnl
IEEE Geosci. Remote. Sens. Lett.
Haining Yang, Tingjun Li, Zhiming He, Qing Huo Liu
2015 J jnl
IEEE Trans. Geosci. Remote. Sens.
Tingjun Li, Haining Yang, Zheng-Ou Zhou
2014 conf
OFC
Haining Yang, Brian Robertson, Daping Chu
2013 conf
OFC/NFOEC
Haining Yang, Brian Robertson, Daping Chu
2010 J jnl
Displays
Jun Xia, Di Qu, Haining Yang, Jiejie Chen, Wenliang Zhu
redb/extractors/database_exporters.py
← Index redb/extractors/database_exporters.py python
from abc import ABC, abstractmethod
from datetime import datetime, timezone
from dataclasses import asdict
import hashlib
import json
import inspect
from typing import Any, Dict, List, Union
from redb import settings
import traceback
from contextlib import contextmanager

class DatabaseExporter(ABC):
    @abstractmethod
    def export(self, data: Any, **kwargs) -> bool:
        """Export data to the database"""
        pass

class ElasticsearchExporter(DatabaseExporter):
    def __init__(self, logger: Any, index_prefix: str):
        self.client = settings.get_elasticsearch_client()
        self.index_prefix = index_prefix
        self.log = logger

    def export(self, data: Any, **kwargs) -> bool:
        self.log.debug(inspect.currentframe().f_code.co_name)
        if not isinstance(data, list):
            data = [data]
            
        now_t = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S")
        index = kwargs.get('index')
        tag = kwargs.get('tag')
        hashes = kwargs.get('hashes')
        
        for dataclass_ in data:
            try:
                # Convert dataclass to dict and filter out None values
                document = {k: v for k, v in asdict(dataclass_).items() if v is not None}
                
                if tag:
                    document["tag"] = tag
                document |= hashes
                document["timestamp_utc"] = now_t
                document["known_benign"] = kwargs.get('known_benign', False)
                document["known_malicious"] = kwargs.get('known_malicious', False)

                if "_id" in document:
                    tmp_id = document.pop("_id") + document["sha256"]
                    _id = hashlib.sha256(tmp_id.encode()).hexdigest()
                else:
                    _id = document["sha256"]

                doc_dump = json.dumps(document)
                self.client.index(index=index, id=_id, document=doc_dump)
                
            except Exception as e:
                self.log.error(f"Failed to export to Elasticsearch: {e}")
                return False
                
        return True

class PrintExporter(DatabaseExporter):
    """Exporter that prints results instead of uploading to database (for dry-run mode)"""
    def __init__(self, logger: Any, index_prefix: str):
        self.index_prefix = index_prefix
        self.log = logger
        self.log.debug(f"PrintExporter initialized with index_prefix: {index_prefix}")

    def export(self, data: Any, **kwargs) -> bool:
        try:
            import json
            from dataclasses import asdict, is_dataclass

            self.log.debug(f"PrintExporter.export called with data type: {type(data)}")

            if data is None:
                self.log.debug("PrintExporter.export: data is None, returning True")
                return True

            if not isinstance(data, list):
                data = [data]

            for i, item in enumerate(data):
                if is_dataclass(item) and not isinstance(item, type):
                    # Convert dataclass instance to dict
                    try:
                        item_dict = asdict(item)
                        print(json.dumps(item_dict, indent=2, default=str))
                    except Exception as e:
                        self.log.error(f"PrintExporter.export: Error converting dataclass: {e}")
                        print(str(item))
                elif isinstance(item, dict):
                    # Already a dict, print as JSON
                    print(json.dumps(item, indent=2, default=str))
                else:
                    # Fallback for other types
                    print(json.dumps(item, indent=2, default=str) if not isinstance(item, str) else item)

            self.log.debug("PrintExporter.export: completed successfully")
            return True
        except Exception as e:
            self.log.error(f"PrintExporter.export: Failed to print data: {e}")
            return False


class ClickHouseExporter(DatabaseExporter):
    def __init__(self, logger: Any, index_prefix: str, client=None):
        self.index_prefix = index_prefix
        self.log = logger
        self.client = client

    @contextmanager
    def clickhouse_connection(self):
        client = settings.create_clickhouse_client()
        try:
            yield client
        finally:
            try:
                client.close()
            except:
                pass
    # def export(self, data: Any, **kwargs) -> bool:
    #     try:
    #         # Handle multi-table export case
    #         # if isinstance(data, dict) and 'multi_table' in data:
    #         #     for table_name, table_data in data.items():
    #         #         if table_name != 'multi_table' and isinstance(table_data, dict) and 'table' in table_data:
    #         #             self.log.debug(f"Exporting to table: {table_data['table']}")
    #         #             self.log.debug(f"Column names: {table_data['column_names']}")
    #         #             self.log.debug(f"Column types: {table_data['column_type_names']}")
    #         #             self.log.debug(f"Data sample: {table_data['data'][0] if table_data['data'] else 'No data'}")
                        
    #         #             try:
    #         #                 result = self.client.insert(
    #         #                     table_data['table'],
    #         #                     table_data['data'],
    #         #                     column_names=table_data['column_names'],
    #         #                     column_type_names=table_data['column_type_names']
    #         #                 )
    #         #                 if not result:
    #         #                     self.log.error(f"Failed to insert into table {table_data['table']}")
    #         #                     return False
    #         #             except Exception as e:
    #         #                 self.log.error(f"Error inserting into table {table_data['table']}: {e}")
    #         #                 self.log.error(f"Data that caused error: {table_data['data']}")
    #         #                 return False
    #         #     return True

    #         if isinstance(data, dict) and 'multi_table' in data:
    #             for table_name, table_data in data.items():
    #                 if table_name != 'multi_table' and isinstance(table_data, dict) and 'table' in table_data:
    #                     self.log.debug(f"Exporting to table: {table_data['table']}")
                        
    #                     # Validate each row before insert
    #                     for row in table_data['data']:
    #                         for val, col_name, col_type in zip(row, table_data['column_names'], 
    #                                                         table_data['column_type_names']):
    #                             # Check for empty strings
    #                             if isinstance(val, str) and not val:
    #                                 self.log.error(f"Empty string found for column {col_name}")
    #                                 raise ValueError(f"Empty string not allowed for column {col_name}")
                                
    #                             # Log all string values for certificate_serial_number
    #                             if col_name == 'certificate_serial_number':
    #                                 self.log.debug(f"Serial number value: '{val}', type: {type(val)}, "
    #                                             f"repr: {repr(val)}")
                        
    #                     try:
    #                         result = self.client.insert(
    #                             table_data['table'],
    #                             table_data['data'],
    #                             column_names=table_data['column_names'],
    #                             column_type_names=table_data['column_type_names']
    #                         )
    #                         if not result:
    #                             self.log.error(f"Failed to insert into table {table_data['table']}")
    #                             return False
    #                     except Exception as e:
    #                         self.log.error(f"Error inserting into table {table_data['table']}: {e}")
    #                         self.log.error(f"Data that caused error: {table_data['data']}")
    #                         return False
    #             return True

    #         # Handle single table case
    #         table = kwargs.get('table')
    #         if not table:
    #             raise ValueError("Table name must be provided for ClickHouse export")
            
    #         # Unpack the tuple returned by prepare_export_data
    #         if isinstance(data, tuple):
    #             if len(data) != 3:
    #                 raise ValueError("Data tuple must contain exactly 3 elements: (data, column_names, column_type_names)")
    #             insert_data, column_names, column_type_names = data
    #         else:
    #             # Use provided column names and types from kwargs
    #             insert_data = data
    #             column_names = kwargs.get('column_names')
    #             column_type_names = kwargs.get('column_type_names')
                
    #         if not (column_names and column_type_names):
    #             raise ValueError("column_names and column_type_names must be provided")

    #         # Ensure data is in list format for batch insert
    #         if not isinstance(insert_data, list):
    #             insert_data = [insert_data]
                
    #         self.client.insert(
    #             table,
    #             insert_data,
    #             column_names=column_names,
    #             column_type_names=column_type_names
    #         )
    #         return True
            
    #     except Exception as e:
    #         self.log.error(f"Failed to export to ClickHouse: {e}")
    #         return False

    def get_client(self):
        """Get existing client or create new one if needed"""
        if self.client:
            return self.client
        try:
            return settings.create_clickhouse_client() 
        except Exception as e:
            self.log.error(f"Failed to create ClickHouse client: {e}")
            return None
            
    # WORKING SIMPLE VERSION
    def export(self, data: Any, **kwargs) -> bool:
        try:
            # # Handle multi-table export case
            # # if isinstance(data, dict) and 'multi_table' in data:
            # #     for table_data in data.values():
            # #         if isinstance(table_data, dict) and 'table' in table_data:
            # #             result = self.client.insert(
            # #                 table_data['table'],
            # #                 table_data['data'],
            # #                 column_names=table_data['column_names'],
            # #                 column_type_names=table_data['column_type_names']
            # #             )
            # #             if not result:  # If any insert fails, return False
            # #                 return False
            # #     return True
            # if isinstance(data, dict) and 'multi_table' in data:
            #     for key, table_data in data.items():
            #         if key != 'multi_table' and isinstance(table_data, dict) and 'table' in table_data:
            #             # Add type hints
            #             typed_data = []
            #             for row in table_data['data']:
            #                 typed_row = []
            #                 for val, type_name in zip(row, table_data['column_type_names']):
            #                     if isinstance(val, str) and not val:
            #                         val = 'UNKNOWN'
            #                     if type_name == 'String' or 'LowCardinality(String)' in type_name:
            #                         val = str(val) if val is not None else 'UNKNOWN'
            #                     typed_row.append(val)
            #                 typed_data.append(typed_row)
                        
            #             table_data['data'] = typed_data
                        
            #             result = self.client.insert(
            #                 table_data['table'],
            #                 table_data['data'],
            #                 column_names=table_data['column_names'],
            #                 column_type_names=table_data['column_type_names'],
            #                 settings={'input_format_values_interpret_expressions': 0}  # Disable type inference
            #             )
            #             if not result:
            #                 return False
            #         return True

            # Get a new client connection for this export operation
            with self.clickhouse_connection() as client:
                if not client:
                    return False

                # LAST WORKING VERSION
                if isinstance(data, dict) and 'multi_table' in data:
                    for key, table_data in data.items():
                        if key != 'multi_table' and isinstance(table_data, dict) and 'table' in table_data:
                            # Debug logging
                            self.log.debug(f"Processing table: {table_data['table']}")
                            self.log.debug(f"Column names: {table_data['column_names']}")
                            self.log.debug(f"Column types: {table_data['column_type_names']}")
                            
                            typed_data = []
                            for row_idx, row in enumerate(table_data['data']):
                                typed_row = []
                                for val_idx, (val, type_name, col_name) in enumerate(
                                    zip(row, table_data['column_type_names'], table_data['column_names'])
                                ):
                                    try:
                                        # Handle different types
                                        if val is None:
                                            if 'Nullable' in type_name:
                                                val = None  # Keep None for Nullable columns
                                            elif 'Array' in type_name:
                                                val = []
                                            elif 'Int' in type_name or 'UInt' in type_name:
                                                val = 0
                                            elif 'FixedString(16)' in type_name:
                                                val = b'\x00' * 16  # Binary FixedString
                                            elif 'String' in type_name or 'LowCardinality' in type_name:
                                                val = 'UNKNOWN'
                                            elif 'DateTime' in type_name:
                                                val = datetime.now(timezone.utc)
                                            elif 'Boolean' in type_name:
                                                val = False
                                            else:
                                                self.log.error(f"Unhandled type {type_name} for null value")
                                                val = 'UNKNOWN'
                                        
                                        # Log problematic values
                                        if isinstance(val, str) and not val.strip():
                                            self.log.warning(f"Empty string found in table {table_data['table']}, "
                                                        f"column {col_name}, row {row_idx}")
                                        
                                        # Ensure array types are always lists
                                        if 'Array' in type_name and not isinstance(val, list):
                                            val = [val]
                                        
                                        typed_row.append(val)
                                    except Exception as e:
                                        self.log.error(f"Error processing value in table {table_data['table']}, "
                                                    f"column {col_name} ({type_name}), "
                                                    f"row {row_idx}, value: {repr(val)}")
                                        raise
                                        
                                typed_data.append(typed_row)
                            
                            table_data['data'] = typed_data

                            # Skip insert if there is nothing to insert
                            if not typed_data:
                                self.log.debug(f"No data to insert for table {table_data['table']}, skipping.")
                                continue

                            # Debug log the first row of data
                            self.log.debug(f"Sample row for {table_data['table']}: {typed_data[0]}")

                            result = client.insert(
                                table_data['table'],
                                table_data['data'],
                                column_names=table_data['column_names'],
                                column_type_names=table_data['column_type_names'],
                                settings={'input_format_values_interpret_expressions': 0}
                            )
                            if not result:
                                self.log.error(f"Insert failed for table {table_data['table']}")
                                return False
                    return True

                # Handle single table case
                table = kwargs.get('table')
                if not table:
                    raise ValueError("Table name must be provided for ClickHouse export")
                
                # Unpack the tuple returned by prepare_export_data
                if isinstance(data, tuple):
                    if len(data) != 3:
                        raise ValueError("Data tuple must contain exactly 3 elements: (data, column_names, column_type_names)")
                    insert_data, column_names, column_type_names = data
                else:
                    # Use provided column names and types from kwargs
                    insert_data = data
                    column_names = kwargs.get('column_names')
                    column_type_names = kwargs.get('column_type_names')
                    
                if not (column_names and column_type_names):
                    raise ValueError("column_names and column_type_names must be provided")

                # Ensure data is in list format for batch insert
                if not isinstance(insert_data, list):
                    insert_data = [insert_data]

                # Skip insert if there is nothing to insert
                if not insert_data:
                    self.log.debug(f"No data to insert for table {table}, skipping.")
                    return True

                client.insert(
                    table,
                    insert_data,
                    column_names=column_names,
                    column_type_names=column_type_names,
                    settings={'input_format_values_interpret_expressions': 0}  # Disable type inference
                )
                return True

        except TypeError as e:
            # Get the actual value causing the error from the exception traceback
            import sys
            exc_type, exc_value, exc_traceback = sys.exc_info()
            
            # Walk through the traceback to find the frame with the problematic value
            current = exc_traceback
            while current:
                if 'string.py' in current.tb_frame.f_code.co_filename and '_data_size' in current.tb_frame.f_code.co_name:
                    locals_dict = current.tb_frame.f_locals
                    problematic_value = locals_dict.get('x')
                    self.log.error(f"TypeError with value: {problematic_value} (type: {type(problematic_value)})")
                    self.log.error(f"Full locals at error: {locals_dict}")
                    break
                current = current.tb_next
            
            self.log.error(f"Failed to export to ClickHouse: {e}")
            self.log.error("Full traceback:")
            self.log.error(traceback.format_exc())
            return False
        except Exception as e:
            self.log.error(f"Failed to export to ClickHouse: {e}")
            self.log.error(traceback.format_exc())
            return False
        finally:
            # Only close if we created a new client
            if client and client != self.client:
                # Close the client connection
                try:
                    client.close()
                except:
                    pass