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Database Chapter 10 Database recovery Technology

mechanism design are: first, how to build redundant data, and secondly, how to use these redundant data to implement database recovery. The implementation technology of recovery Data dumps Data dumps are the basic technique used in database recovery, where a DBA periodically copies an entire database to a tape or another disk. Dumps are time-consuming and resou

How to Use adplus to dump the memory of a process

As mentioned above, the dump file can save the Process status for easy analysis. Because the dump file records the specific information of a process at a certain time point, it is very important to save the dump. For exampleProgramCrash: dump should be obtained when the command that causes the crash is executed (that is, when the 1st chance exception occurs), so that the direct cause of the problem can be seen during dump analysis. Adplus is a vbs script in the same directory as windbg. Adplus

JSON overview and Python-related operations on JSON (GO)

bandwidth, so the appropriate time also to compress the data. The separator parameter can play the role of a tuple that contains a string that splits the object.print ' data: ', repr (data) print ' repr (data): ', Len (repr (data)) print ' Dumps (data): ', Len (json.dumps (data)) print ' Dumps (data, indent=2): ', Len (json.dumps (data, indent=4)) print ' Dumps

A little harvest of Python json, a custom serialization method

$ python json_simple_types.py DATA: [{' A]: ' A ', ' C ': 3.0, ' B ': (2, 4)}] JSON: [{"A]: "A", "C": 3.0, "B": [2, 4]}] The value obtained by decoding after encoding may not be exactly the same as the original object. [python] view plain copy import JSON data = [{' A ': ' A ', ' B ':(2, 4), ' C ': 3.0}] data_string = Json.dumps (dat A) print ' encoded: ', data_string decoded = Json.loads (data_string) print ' decoded: ', decoded print ' ORIGINAL: ', Ty PE (data[0][' B ']) print ' decoded: ', t

WebGis application development framework

}53 if (_ baseURL = "t @ 128 ")54 {55 url = "http: // mt" + (col % 4) + ".google.cn/vt/lyrs=" + _ baseURL + ", r @ 169000000 v = w2.114 hl = zh-CN gl = cn "+" x = "+ col +" "+" y = "+ row + " "+" z = "+ level +" s = Galil ";56}57 if (_ baseURL = "m @ 161000000 ")58 {59 url = "http: // mt" + (col % 4) + ".google.cn/vt/lyrs=" + _ baseURL + " v = w2.114 hl = zh-CN gl = cn " + "x =" + col + "" + "y = "+ row +" "+" z = "+ level +" s = Galil ";60}61 return new URLRequest (url );62}6364 priva

Python serialization module JSON and Pickle

Serialization related 1. Json Application Scenarios: The JSON module is primarily used to process data in JSON format, can convert JSON-formatted data into a Python dictionary, facilitates python processing, and can convert objects such as a Python dictionary or list into JSON-formatted data for cross-platform or cross-language data interaction Function: The JSON module provides four functions: dumps, dump, loads, load

On disaster recovery of geographically dispersed parallel systems

reduces the time that is not available to the database for backup copies. In many cases, the time savings are measured in hours, and concurrent copies greatly increase the flexibility of the scheduling of online operations and batching in a os/390 environment. Prior to the occurrence of concurrent copies, alternate transposition between physical and logical information dumps is often required. In the dump process, the data is not available for other

"Translated from MoS article" under Win2003 SP1, encountering unexplained database performance degradation

Translated from MoS article: Under Win2003 SP1, encountering unexplained database performance degradationUnexplained Database slowdown Seen on Windows 2003 Service Pack 1 (Doc ID 464683.1)Applies To:Oracle server-enterprise edition-version 9.2.0.1 to 11.1.0.6 [Release 9.2 to 11.1]Z*obsolete:microsoft Windows Server 2003Microsoft Windows Itanium (64-bit)Z*obsolete:microsoft Windows XP (64-bit AMD64 and Intel EM64T)Microsoft Windows Server 2003 (64-bit Itanium) Microsoft Windows Server 2003Microso

Python learning path ----- serialization, python ----- serialization

Python learning path ----- serialization, python ----- serialization The process of changing variables from memory to storage or transmission is called serialization. in Python, it is called pickling. In other languages, it is also called serialization, alling, flattening, and so on. After serialization, The serialized content can be written to the disk or transmitted to another machine over the network. In turn, it is called deserialization to re-read the variable content from the serialized ob

A brief talk on Python Simplejson module

performance. Below we discuss the provided interface, and only show the necessary parameters, the other keyword parameters will be expressed as **kwargs; Simplejson. Dump (obj, fp, **kwargs): Writes Python objects to a file (in JSON format) Simplejson. dumps (obj, **kwargs): Represents a Python object as a string (in JSON format) Simplejson. Load (FP, **kwargs): read from a file (containing a JSON structure) as a Python object Simplejson. l

Python serialization: JSON & Pickle & Shelve Module

One, JSON Pickle Shelve ModuleJSON, used to convert between string and Python data typesPickle for conversion between Python-specific types and Python data typesThe JSON module provides four functions: dumps, dump, loads, loadThe Pickle module provides four functions: dumps, dump, loads, loadJSON module:Here are some examples to learn:First, let's look at the JSON dum

Python3 Serialization Module (JSON, Pickle, shelve)

Serialization modulePurpose of serialization1. Persist the custom object in some form of storage;2. Transfer objects from one place to another. 3, make the program more maintenance. 1.jsonThe JSON module provides four functions: dumps, dump, loads, loadImportJSON #(1) Dumps DIC = {'K1':'value 1','K2':'Value 2','K3':'Value 3'}str_dic= Json.dumps (DIC)#Convert a dictionary to a stringPrint(Type (str_dic), str

Analyzing memory management problems with memory Dump diagnostic for Java (MDD4J)

data structure views to help you track changes in memory consumption while revising bugs, adding or removing new features. MDD4J can be obtained through IBM Support Assistant. Because memory heap analysis consumes a large amount of processor and I/O resources, you can also run it outside of the IBM Support Assistant Workbench. Performing memory heap analysis on a server class machine--especially 64-bit machines--allows you to handle an infinite amount of memory heap and reserve a large amount

Pg_dump Example Detailed

need to be recovered before they are restored. Archive files can also be ported across platforms.D:\Program Files\powercmd>pg_dump--helpPg_dump dumps a database to a plain text file or to a different format.Usage: pg_dump [options] ... [Database name]General Options:-F,--file=filename output file or directory name-F,--format=c|d|t|p output file format (custom, directory, tar, plain text)-V,--verbose verbose mode-Z, compression level of--compress=0-9

Pgsql backup pg_dump and restore Pg_restore

, no output mode (data definition).This option is only meaningful for plain text formatting. For the archive format, you can declare options when calling Pg_restore.-B--blobsContains large objects in the dump. You must select a non-text output format.-C--cleanOutputs the command to clean (delete) The database object before creating the database Creation command.This option is only meaningful for plain text formatting. For the archive format, you can declare options when calling Pg_restore.-C--cr

Several organization forms of interface Testing

Registration Interface Test 1. Single interface test # encoding = utf-8import requestsimport jsondata = {'username': 'test001', 'Password': 'wulaoshi12345 ', 'address ': '[email protected]'} DATA = JSON. dumps (data) RES = requests. post ('HTTP: // 39.106.41.11: 8080/register/', data) print (res. text) print (res. status_code) print (res. JSON () 2. Single interface with assertion # encoding = utf-8import requestsimport jsonimport repattern = Re. com

Python shelve module

Import Shelveimport datetimed = Shelve.open (' shelve_test ') ' Write file ' ' info = {' age ': ' ' job ': ' IT '}name = [' Jack ', ' Rose '] d[' name '] = named[' info '] = infod[' data '] = Datetime.datetime.now () d.close () ' Read file ' d = shelve.open (' shelve_test ') Print (D.get (' name ')) print (D.get (' info ')) print (D.get (' Date ')) D.close ()As you can see, the shelve module and JSON work well for the file, but there are three files when you save the file,Do not care about the f

Introduction to Java Heap dump file analysis tool Jhat

Jhat is the Java Heap analysis tool (Java heap analyzes tools). Become standard after Jdk6u7. Using this command requires some Java development experience, and the official does not provide technical support and customer service for this tool.Usage:jhat [Options] Heap-dump-file Parameters: options Optional command line parameters, please refer to the options below Heap-dump-fileBinary Java heap dump files to view (Java binary heap dump file). If a dump file contains more than one heap

Database principles-Data recovery

1. How to set up redundant data Data dump (Backup) Log in log file (logging) 1. Data dumpsCharacteristics: The backup copy can be re-loaded after the database has been compromised Reloading a backup copy only restores the database to the state at the time of the dump Method: Static dumps and dynamic dumps Mass

My views on Enterprise Architecture Communication

process models. EBA (Enterprise Business Architecture) What is the relationship with GRC (governance, risk and compliance? Recently, Gartner symposium/itxpo in France pointed out that companies that do not face information management and do not coordinate with information management are more than 90% likely to fail within a year or two. Based on an in-depth analysis of EBA that may address the pain points of GRC, we recently submitted a briefing and listened to conversations with near

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