Log parser 2 2

Author: m | 2025-04-24

Install Microsoft Log Parser and Log Parser Studio . 1. Download and install Log Parser 2.2. 2. Download Log Parser Studio. This will be in a .ZIP file. 3. Unzip Log Parser Step 2: Enter Parser Name, Log File Path. 3 Step 2: Enter Parser Name, Log File Path. Enter the following: Parser name - The name of this log parser definition. Log File Path - The full path of

Log Parser Lizard (2 Downloads) - Zedload

CalcexA simple mathematical expression parser and evaluator for .NET.This repository contains calcex.core, the actual .NET parser library, the calcex .NET Core CLI and a sample Windows GUI.OverviewCalcex.Core is a basic parser and evaluator library for mathematical expressions built on .NET Core.Some functionalities are:support for many common arithmetic and bitwise operators (*, ^, %, &, ...)support for many mathematical functions (sin, ln, log, min, ...)user-defined variables and functionsevaluate to double, decimal or boolean valuescompile expressions into callable delegatesconvert expressions to postfix notation and MathML stringsCalcex.Console contains a simple command-line interface that provides easy access to the mathematical evaluators.Calcex.Windows contains Calcex App, a basic GUI calculator app for Windows built using WPF.How To (Calcex.Core)Simple example func = tree.Compile("x");">Parser parser = new Parser();// Set a custom variableparser.SetVariable("x", -12);// Parsevar tree = parser.Parse("2*pi+5-x");// Evaluate to doubledouble doubleResult = tree.Evaluate();// Evaluate to decimaldecimal decimalResult = tree.EvaluateDecimal(); // Compile to delegateFuncdouble, double> func = tree.Compile("x");Fore more, visit the Calcex wiki.LicenseCalcex is published under BSD-3-Clause license.

Log Parser - Log Parser Documentation

The Great C++ Mathematical Expression Parser BenchmarkThis is a benchmark suite for different implementations of open source mathexpression parsers and evaluators written in C++. Currently the followingexpression parsers are part of this benchmark:#LibraryAuthorLicenseNumeric Type00ATMSPHeinz van SaanenGPL v3double, MPFR01ExprTkArash PartowMITdouble, float, MPFR02FParserJuha Nieminen & Joel YliluomaLGPLdouble03LeptonPeter EastmanMITdouble04MathExprYann OllivierCopyright Notice 1997-2000double05METLTill HeinzelApachedouble06MTParserMathieu JacquesCPOLdouble07muParserIngo BergMITdouble, float08muParserXIngo BergMITdouble, float09TinyExprLewis Van WinkleZlibdoubleNote: The terms double, float etc found in the table above are defined as follows:double : IEEE-754 Double-Precision Binary Floating-Point (64-bit)float : IEEE-754 Single-precision floating-point format (32-bit)MPFR : GNU Multiple Precision Floating-Point ReliablyNote: This archive is not meant as a primary source for any of the librarieslisted above as it may contain outdated versions of said libraries.ObjectivesAll the parsers in this benchmark suite are in one way or another POEM(Parse Once Evaluate Many times) in nature. As such the primaryobjectives for this benchmark are to ascertain the followingproperties for each of the denoted parsers in following order ofpriority:Correctness and precision of results relative to the floating point type usedRobustness of the parser given various mathematical expressionsEvaluation efficiency of 'compiled/parsed' expressionsThe SetupThe benchmark takes two parameters:Number of iterations (N)Benchmark Test FileThe mathematical expression benchmark files are as follows:bench_expr.txtbench_expr_all.txtbench_expr_all_permutations.txtbench_expr_complete.txtbench_expr_extensive.txtbench_expr_precedence.txtbench_expr_random_with_functions.txtbench_expr_random_without_functions.txtbench_expr_weird.txtThe following is a short sampling of expressions taken from the bench_expr.txtexpression suite:a+1.1a*2.22.2*a+1.1(2.2*a+1.1)*3.3sin(2.2 * a) + cos(pi / b)1 - sin(2.2 * a) + cos(pi / b)sqrt(1 - sin(2.2 * a) + cos(pi / b) / 3.3)(a^2 / sin(2 * pi / b)) -a / 2.21-(a/b*0.5)e^log(7*a)10^log(3+b)(cos(2.41)/b)-(sin(pi+a)+1)a-(e^(log(7+b)))As an example, the following execution will use the"bench_expr_all.txt"set of expressions, executing each expression 100000 times:ParserBench.exe 100000 bench_expr_all.txtThe RoundsFor every expression in the benchmark file, every parser evaluates the givenexpression N times, this is known as a round. The total time each parser takesto evaluate the expression N times is recorded. Ranking of the parsers forthe round is done from the fastest to the slowest. The following is an examplesummary for the expression '(a^2/sin(2*pi/b))-a/2':Expression 64 of 70: "(a^2/sin(2*pi/b))-a/2"; Progress: #############[01] ExprTkFloat ( 34.144 ns, 3.744852304458618164, -15768714.994192123413085938)[02] ExprTk ( 39.963 ns, 3.744853294789905362, -15768714.840563148260116577)[03] muparserSSE ( 40.698 ns, 3.744852304458618164, -15768715.739250183105468750)[04] muparser 2.2.4 ( 47.358 ns, 3.744853294789905362, -15768714.840563148260116577)[05] muparser 2.2.4 (omp) ( 53.252 ns, 3.744853294789905362, -15768714.840563148260116577)[06] FParser 4.5 ( 60.614 ns, 3.744853294789905362, -15768714.840563148260116577)[07] atmsp 1.0.4 ( 64.374 ns, 3.744853294789905362, -15768714.840563148260116577)[08] METL ( 79.018 ns, 3.744853294789905362, -15768714.840563148260116577)[09] MTParser ( 80.352 ns, 3.744853294789905362, -15768714.840563148260116577)[10] MathExpr (114.392 ns, 3.744853294789905362, -15768714.840563148260116577)[11] TinyExpr (121.184 ns, 3.744853294789905362, -15768714.840563148260116577)[12] Lepton (297.673 ns, 3.744853294789905362, -15768714.840563148260116577)[13] muparserx (498.809 ns, 3.744853294789905362, -15768714.840563148260116577)Parsers that can't parse the

Log Parser Studio 2 released : r/sysadmin - Reddit

01:56:46 17408 bytes kstvtune.ax: 5.03.2600.2180 English Final Retail 8/4/2004 01:56:58 61952 bytes ksxbar.ax: 5.03.2600.2180 English Final Retail 8/4/2004 01:56:58 43008 bytes kswdmcap.ax: 5.03.2600.2180 English Final Retail 8/4/2004 01:56:58 90624 byteswstcodec.sys: 5.03.2600.2180 English Final Retail 8/4/2004 00:10:22 19328 byteswstdecod.dll: 5.03.2600.2180 English Final Retail 8/4/2004 01:56:48 50688 bytes msdv.sys: 5.03.2600.2180 English Final Retail 8/4/2004 00:10:00 51328 bytes------------------DirectShow Filters------------------DirectShow Filters:WMAudio Decoder DMO,0x00800800,1,1,,WMAPro over S/PDIF DMO,0x00600800,1,1,,WMSpeech Decoder DMO,0x00600800,1,1,,WMVideo Advanced Decoder DMO,0x00800001,1,1,,Mpeg4s Decoder DMO,0x00800001,1,1,,WMV Screen decoder DMO,0x00800001,1,1,,WMVideo Decoder DMO,0x00800001,1,1,,Mpeg43 Decoder DMO,0x00800001,1,1,,Mpeg4 Decoder DMO,0x00800001,1,1,,WMT MuxDeMux Filter,0x00200000,0,0,wmm2filt.dll,2.01.4026.0000Vorbis 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Decoder,0x00800000,1,1,qdv.dll,6.05.2600.2180Windows Media Update Filter,0x00400000,1,0,wmpasf.dll,10.00.0000.3802ASF DIB Handler,0x00600000,1,1,wmpasf.dll,10.00.0000.3802ASF ACM Handler,0x00600000,1,1,wmpasf.dll,10.00.0000.3802ASF ICM. Install Microsoft Log Parser and Log Parser Studio . 1. Download and install Log Parser 2.2. 2. Download Log Parser Studio. This will be in a .ZIP file. 3. Unzip Log Parser

Log Parser Lizard : Log Parser GUI

Chuyển đến nội dung chính Trình duyệt này không còn được hỗ trợ nữa. Hãy nâng cấp lên Microsoft Edge để tận dụng các tính năng mới nhất, bản cập nhật bảo mật và hỗ trợ kỹ thuật. IIS Logs and Log Parser Studio Reports Bài viết01/26/2023 Trong bài viết này -->Applies to: Exchange Server 2013Analyzing Log Parser Studio ReportsLog Parser Studio is a utility that allows you to search through and create reports from several types of log files, including those for Internet Information Services (IIS). It builds on top of Log Parser 2.2 and has a full user interface for easy creation and management of related SQL queries.Download Log Parser Studio and then review Introducing: Log Parser Studio.Remember that in Exchange 2013, all traffic has to go through IIS. This means analyzing IIS logs is the best way to get a complete picture of the number of connections that are hitting a server, of protocol-specific information about the connections, and of the users who are most impacting performance. Over twenty new reports have been developed for Log Parser Studio, for the purpose of troubleshooting Exchange 2013 performance issues.Log Parser Studio Reporting for Exchange 2013 Performance IssuesTo gain a comprehensive understanding of overall load in your Exchange 2013 environment, use the following reporting and compare the numbers against each server.The Log Parser Studio download .zip file contains the Log Parser Studio reports listed here, and additional troubleshooting-related reports.IIS: Requests Per Hour. Feed in IIS logs from either the Default Web Site (W3SVC1 directory) or the Backend Website (W3SVC2 directory), but not both at the same time.ACTIVESYNC_WP: Clients by percent. Calculates all ActiveSync requests broken down by user-agent and percentage of each client to the total number of requests.ACTIVESYNC_WP: Requests per hour (CSV). Lists the ActiveSync requests per hour and sends the results to a CSV file.ACTIVESYNC_WP: Requests per user (CSV). Lists ActiveSync requests per user and sends the results to a CSV file.ACTIVESYNC_WP: Requests per user (Top 10k). Lists ActiveSync requests per user for the top 10,000 users.ACTIVESYNC_WP: Top Talkers (CSV). Lists the top ActiveSync clients from highest to lowest request count and sends the result to a CSV file.EWS_WP: Clients by percent. Calculates all EWS requests broken down by user-agent and percentage of each client to the total number of requests.EWS_WP: Requests per hour (CSV). Lists the total number of EWS requests per hour.EWS_WP: Requests per user (CSV). Lists EWS requests per user and sends the results to a CSV file.EWS_WP: Requests per user (Top 10k). Lists EWS requests per user for the top 10,000 users.EWS_WP: Top Talkers (CSV). Lists the top EWS clients from highest to lowest request count.OLA_WP: Errors, per user, per hour, per day. Outlook

Log Parser (Log Parser Queries Note)

Identify the resulting log entries. The outer element must be an object.In the example above, the outer element is "entries". Using this, we can define our conversion pattern as:{ entries: [ { "firstName":"%S{First Name}", "lastName":"%S{Last Name}", "employeeId":"%S{Employee Id}", "dateJoined":"%d" } ]}If the outer object containing our log entries was a child of another object, it would not be necessary define the additional outer object. LogViewPlus will always traverse an object hierarchy automatically. Log entry identifiers only need to exist at the log entry root.Compact Log Event Format (CLEF)LogViewPlus is a great tool for viewing CLEF log entries, for example messages created by Serilog. CLEF stands for Compact Log Event Format and it is a method of producing log entries where the log message data is extracted and stored as separate fields withing the log entry. This helps ensure the log entries are machine readable.You can view CLEF log messages in LogViewPlus by adding a parser hint when processing the JSON message. For example, consider the following CLEF log entry:{ "@t": "2020-04-25T04:03:29.3546056Z", "@mt": "Connection id '{Id}' accepted.", "Properties": { "Id": "0HMA0H" }}This log entry can be parsed using the JSON parser and the pattern:{ "@t": "%d", "@mt": "%m{-parserhint:CLEF}" }Notice that the pattern configuration contains a parser hint which is including using the special parameter -parserhint:CLEF. This instruction tells the parser that the log entry message may be formatted to include data from within the JSON message. The included data may be found either at the root level or (more commonly) within a 'Properties' child element.Parsing our sample log entry using the CLEF parser hint will produce a log entry message that is easier to read. In our example, this message would be:Connection id '0HMA0H' accepted.Notice how the connection ID has been extracted from the property data and inserted into the log entry message.

Log Parser Help - Log Parser Documentation

JSON ParserNew to LogViewPlus? Find out more about how you can use LogViewPlus to help you analyze JSON log files.LogViewPlus has a built in JSON parser which is capable of analyzing your JSON log files. It does this by parsing your JSON file according to a template. A template is a sample JSON log entry that has certain fields identified with Conversion Specifiers.LogViewPlus will not parse an entire log file as JSON. Rather, it will parse the log file line by line while checking the input structure. Only when the structure represents a complete JSON object will a parse be attempted. This approach allows for monitoring JSON log files in tail mode, but may cause issues if your JSON log is a single block of text without new lines.Because each log entry is parsed separately, our template will only need to match a single log entry. For example, let's look at a simple JSON log enry:{ "firstName":"John", "lastName":"Doe", "employeeId":"12345", "other":"ignore me", "dateJoined":"2014-05-16 10:50:14,125"} This is a JSON log entry with five fields: firstName, lastName, employeedId, other, and dateJoined. What we need to do is replace the field data with a Conversion Specifier that identifies the field data type. This might give us the following mapping.JSON FieldConversion SpecifierLogViewPlus ColumnfirstName%S{First Name}First NamelastName%S{Last Name}Last NameemployeeId%s{Employee Id}Employee IdotherWe want to ignore this field.dateJoined%dDate and TimeTherefore, we could parse this JSON log entry with the template:{ "firstName":"%S{First Name}", "lastName":"%S{Last Name}", "employeeId":"%s{Employee Id}", "dateJoined":"%d"}Notice that in the above template the "other" field has been ignored. To ignore a field we simply do not include it in our template. If one of the elements we were interested in had been a child of a parent node, we would have needed to include the parent node in our template. The important thing is that the template has the full path to the target node.Once we load this template into LogViewPlus it will appear as:To do this, we just need to give LogViewPlus our parsing template as an argument for the JSON parser. We can do this in Parser Mappings:White space will be ignored, so we are free to format the JSON as needed.If our log file contained multiple log entries, LogViewPlus would expect them all to have the same format. New log entries should also be separated by a new line as discussed above.Log files parsed with the JSON parser support automatic pretty-printing by default.Finally, notice the similarities between the JSON Parser and the XML Parser discussed in the next section. Both use the concept of templates, so once you have learned one you have basically learned the other.Parsing Embedded JSONLogViewPlus v2.5.56 and greater can parse JSON log entries are embedded within a parent object. For example, consider the JSON log file:{ logid: "App Log 1", entries: [ { "firstName":"John", "lastName":"Doe", "employeeId":"12345", "other":"ignore me", "dateJoined":"2014-05-16 10:50:14,125" }, { ... } ]}Our conversion pattern for this log file will largely look the same as before with one crucial difference. We must specify the outer element which will act to. Install Microsoft Log Parser and Log Parser Studio . 1. Download and install Log Parser 2.2. 2. Download Log Parser Studio. This will be in a .ZIP file. 3. Unzip Log Parser Step 2: Enter Parser Name, Log File Path. 3 Step 2: Enter Parser Name, Log File Path. Enter the following: Parser name - The name of this log parser definition. Log File Path - The full path of