Dell R610 with consumer SSDs in RAID 10

Hello

We have two old servers running Consumer Grade 1 TB SSD hard drives last year without any problems. However, we now want to use Intel DC Enterprise SSDs.

As a RAID 10 server, I would like to know that if we remove an SSD and use a different SSD with the same size but different brands, then it will. Speak of Crucial MX500 1 TB on Intel DC 960 GB and it will be rebuilt. Will it be successfully restored and can we continue until all drives are replaced by Intel DC SSDs?

Is this a possible option or a dangerous one

Extend the functionality of existing classes without damaging the consumer code

Here are a number of classes that are used to create from where Clause for SQL Server and Oracle for different field types, eg. text. numeric and date,

public interface IConditionBuilder
{
bool CanHandle (FilterAction filterAction);

string BuildCondition (SearchCondition filterCondition);
}

public abstract class ConditionBuilder : IConditionBuilder where TContext: FieldSearchContext
{
public abstract string OperatorSymbol {get; }

public string BuildCondition (SearchCondition searchCondition)
{
var conditionBuilder = new StringBuilder ();

var context = searchCondition.GetContext();

conditionBuilder.Append (context.FieldId);
conditionBuilder.Append (OperatorSymbol);
conditionBuilder.Append (GetValue (context));

return conditionBuilder.ToString ();
}

public abstract bool CanHandle (FilterAction filterAction);

public abstract object GetValue (TContext context);

}

public class TextLikeConditionBuilder: ConditionBuilder
{
public override string OperatorSymbol => "LIKE";

public override bool CanHandle (FilterAction action) => action == FilterAction.TextLike;

public override object GetValue (TextContext context)
{
if (context.Text == null)
{
return zero;
}

return string.Concat ("%", context.Text, "%");
}
}

public class TextEqualsConditionBuilder: ConditionBuilder
{
public override string OperatorSymbol => "=";

public override bool CanHandle (FilterAction action) => action == FilterAction.TextEqual;

public override object GetValue (TextContext context)
{
if (context.Text == null)
{
return zero;
}

return "& # 39;" + context.Text + "& # 39;";
}
}

public class NumericLessThanConditionBuilder: ConditionBuilder
{
public override string OperatorSymbol => " < ";

    public override bool CanHandle(FilterAction action) => action == FilterAction.NumericLessThan;

public override object GetValue (NumericContext Context)
{
return context.Number;
}
}

Public class DateGreaterThanAndLessThanEqualConditionBuilder: IConditionBuilder
{
public const string GREATER_THAN = ">";

public const string LESS_THAN_EQUAL = "<=";

public string BuildCondition (SearchCondition filterCondition)
{
var conditionBuilder = new StringBuilder ();

var context = filterCondition.GetContext();

conditionBuilder.Append (context.FieldId);
conditionBuilder.Append (GREATER_THAN);
conditionBuilder.Append ("& # 39;" + context.FromDate + "& # 39;");
conditionBuilder.Append (LESS_THAN_EQUAL);
conditionBuilder.Append ("& # 39;" + context.EndDate + "& # 39;");
return conditionBuilder.ToString ();
}

public bool CanHandle (FilterAction action) => action == FilterAction.DateGreaterThanLessThan;

}

I would like to extend the functionality to purge context.FieldId before creating it condition Statement for e.g. These classes create a statement like Name = & # 39; Aashish & # 39;I want the classes to create statement as [Name] = & # 39; Aashish & # 39;, These classes are used by other developers, so I do not want to restrict consumer functionality because of the changes I'm about to make. Basically, the open-closed principle applies. So, here's how I implemented these changes. Notice how I added a virtual feature SanitizeFieldId in the Condition Builder and DateGreaterThanAndLessThanEqualConditionBuilder,

public abstract class ConditionBuilder : IConditionBuilder where TContext: FieldSearchContext
{
public abstract string OperatorSymbol {get; }

public string BuildCondition (SearchCondition searchCondition)
{
var conditionBuilder = new StringBuilder ();

var context = searchCondition.GetContext();

conditionBuilder.Append (SanitizeFieldId (context.FieldId));
conditionBuilder.Append (OperatorSymbol);
conditionBuilder.Append (GetValue (context));

return conditionBuilder.ToString ();
}

public abstract bool CanHandle (FilterAction filterAction);

public abstract object GetValue (TContext context);

protected virtual string SanitizeFieldId (string fieldId)
{
return fieldId;
}
}

Public class DateGreaterThanAndLessThanEqualConditionBuilder: IConditionBuilder
{
public const string GREATER_THAN = ">";

public const string LESS_THAN_EQUAL = "<=";

public string BuildCondition (SearchCondition filterCondition)
{
var conditionBuilder = new StringBuilder ();

var context = filterCondition.GetContext();

conditionBuilder.Append (SanitizeFieldId (context.FieldId));
conditionBuilder.Append (GREATER_THAN);
conditionBuilder.Append ("& # 39;" + context.FromDate + "& # 39;");
conditionBuilder.Append (LESS_THAN_EQUAL);
conditionBuilder.Append ("& # 39;" + context.EndDate + "& # 39;");
return conditionBuilder.ToString ();
}

public bool CanHandle (FilterAction action) => action == FilterAction.DateGreaterThanLessThan;

protected virtual string SanitizeFieldId (string fieldId)
{
return fieldId;
}
}

public class SanitizedFieldConditionBuiler : ConditionBuilder Where: TContext: FieldSearchContext
{
private ConditionBuilder _baseConditionBuilder;
private IColumnSanitizer _columnSanitizer;

public SanitizedFieldConditionBuiler (ConditionBuilder baseConditionBuilder, IColumnSanitizer columnSanitizer)
{
_baseConditionBuilder = baseConditionBuilder;
_columnSanitizer = columnSanitizer;
}

public override string OperatorSymbol => _baseConditionBuilder.OperatorSymbol;

public override bool CanHandle (FilterAction filterAction) => _baseConditionBuilder.CanHandle (filterAction);

public override object GetValue (TContext context) => _baseConditionBuilder.GetValue (context);

protected override string SanitizeFieldId (string fieldId)
{
return _columnSanitizer.Sanitize (fieldId);
}
}

public class SanitizedDateFieldGreaterThanAndLessThanEqualConditionBuilder: DateGreaterThanAndLessThanEqualConditionBuilder
{
private IColumnSanitizer _columnSanitizer;

public SanitizedDateFieldGreaterThanAndLessThanEqualConditionBuilder (IColumnSanitizer columnSanitizer)
{
_columnSanitizer = columnSanitizer;
}

protected override string SanitizeFieldId (string fieldId)
{
return _columnSanitizer.Sanitize (fieldId);
}
}

I use extension methods to initialize SanitizedFieldConditionBuilerand SanitizedDateFieldGreaterThanAndLessThanEqualConditionBuilderAs shown below:

public static class extensions
{
public static SanitizedFieldConditionBuiler SanitizeField(This ConditionBuilder source, IColumnSanitizer columnSanitizer) where TContext: FieldSearchContext
{
Return the new SanitizedFieldConditionBuiler(Source, columnSanitizer);
}

public static SanitizedDateFieldGreaterThanAndLessThanEqualConditionBuilder SanitizeField (this IConditionBuilder source, IColumnSanitizer columnSanitizer)
{
return new SanitizedDateFieldGreaterThanAndLessThanEqualConditionBuilder (columnSanitizer);
}

}

Disinfection is available via an interface IColumnSanitizer and has two different implementations, for SQL Server and Oracle

    public interface IColumnSanitizer
{
string sanitize (string columnName);
}

public class SqlSanitizer: IColumnSanitizer
{
public string sanitize (string columnName)
{
Return "[" + columnName + "]";
}
}

public class OracleSanitizer: IColumnSanitizer
{
public string sanitize (string columnName)
{
return "" "+ columnName +"  "";
}
}

The following describes how to implement context classes:

public abstract class FieldSearchContext
{
public virtual string FieldId {get; }

protected FieldSearchContext (string fieldId)
{
FieldId = fieldId;
}
}

public class DateContext: FieldSearchContext
{
public DateContext (string fieldId, DateTime? fromDate, DateTime? endDate): base (fieldId)
{
FromDate = fromDate;
EndDate = endDate;
}

public DateTime? FromDate {get; }

public DateTime? EndDate {get; }
}

public class TextContext: FieldSearchContext
{
public TextContext (string fieldId, string text): base (fieldId)
{
Text = text;
}

public string text {get; }
}

public class NumericContext: FieldSearchContext
{
public NumericContext (string fieldId, decimal): base (fieldId)
{
Number = number;
}

public decimal {get; }
}

These changes work fine, but I want to find out if this can be achieved in a different and better way.

Use the following code to see it in action:

    Class program
{
static gap Main (string[] arguments)
{
var conditions = new List()
{
new SearchCondition (new NumericContext ("Numeric Field", 1234), FilterAction.NumericLessThan),
new search condition (new TextContext ("Text Field", "ASDF"), FilterAction.TextEqual),
new search condition (new TextContext ("Text Field", "QWERTY"), FilterAction.TextLike),
new search condition (new DateContext ("Date Field", DateTime.Now, DateTime.Now.AddYears (1)), FilterAction.DateGreaterThanLessThan)
};

Console.WriteLine (BuildWhereClause (Operation.AND, Conditions));
Console.Read ();
}

private static string BuildWhereClause (Operation operation, IList Conditions)
{
var returnValue = new list();
var conditionBuilders = new list()
{
new TextEqualsConditionBuilder (). SanitizeField (new SqlSanitizer ()),
new NumericLessThanConditionBuilder (). SanitizeField (new SqlSanitizer ()),
new TextLikeConditionBuilder (). SanitizeField (new SqlSanitizer ()),
new DateGreaterThanAndLessThanEqualConditionBuilder (). SanitizeField (new SqlSanitizer ())
};

foreach (var condition in conditions)
{
var context = condition.GetContext();
var conditionBuilder = conditionBuilders.FirstOrDefault (u => u.CanHandle (condition.FilterAction));
returnValue.Add (conditionBuilder.BuildCondition (condition));
}

if (returnValue.Any ())
return string.Join (Convert.ToString ("" + operation + ""), returnValue);

return string.Empty;
}
}

enum operation: int
{
AND = 1,
OR = 2
}

[GET] Digital Marketing Analytics: Making consumer data tangible in a digital world (Que Biz-Tech)

Good news: your competitors have none. It is difficult! But digital marketing analytics are 100% feasible, offering tremendous opportunities. and all data is accessible to you, Chuck Hemann and Ken Burbary help you get the problem right size, solve every piece of the puzzle, and integrate an almost smooth system for transitioning from data to decision making, from actions to results! Take advantage of the opportunities, choose your tools, learn to listen, set the right metrics and distill your digital data to get the most value for everything, from R & D to CRM to Social Media Marketing!
[​IMG]
* Prioritize – because you can not measure, hear and analyze everything
* Use the analysis to gain experience deeply reflect the needs, expectations and behaviors of each client
* Measure up real Social Media ROI: Sales, Leads, and Customer Satisfaction
* Track the performance of all paid, earned and own social media channels
* Use "Hördaten" far beyond PR and marketing: for strategic planning, product development and human resources
* Start optimizing web and social content Real time
* Implement advanced tools, processes, and algorithms to accurately measure impact
* Integrate paid and social data to make more of both
* Use surveys, focus groups and synergies from offline research
* Focus on new marketing and social media investments where they bring the most value

Foreword by Scott Monty
Global Head of Social Media at Ford Motor Company
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Good news: your competitors have none. It is difficult! But digital marketing analytics are 100% feasible, offering tremendous opportunities. and all data is accessible to you, Chuck Hemann and Ken Burbary help you get the problem right size, solve every piece of the puzzle, and integrate an almost smooth system for transitioning from data to decision making, from actions to results! Take advantage of the opportunities, choose your tools, learn to listen, set the right metrics and distill your digital data to get the most value for everything, from R & D to CRM to Social Media Marketing!
[​IMG]

* Prioritize – because you can not measure, hear and analyze everything
* Use analysis to gain experience deeply reflect the needs, expectations and behaviors of each client
* Measure up real Social Media ROI: Sales, Leads, and Customer Satisfaction
* Track the performance of all paid, earned and own social media channels
* Use "Hördaten" far beyond PR and marketing: for strategic planning, product development and human resources
* Start optimizing web and social content Real time
* Implement advanced tools, processes, and algorithms to accurately measure impact
* Integrate paid and social data to make more of both
* Use surveys, focus groups and synergies from offline research
* Focus on new marketing and social media investments where they bring the most value

Foreword by Scott Monty
Global Head of Social Media at Ford Motor Company
DOWNLOAD

Streaming – Configure Spark as a kafka consumer problem SCALA

hello all here are my code I try to configure sparks as a kafka consumer, but I have the error exception
First problem is that the web UI binds to 0.0.0.0 or a native ip: 4040, which I can not find in the browser issue. I will write it in the lower section. Thanks for your help:

######################################## ####### ## #### "" ""

import org.apache.spark.sql.functions._
import org.apache.spark.sql.SparkSession
object Teal extends App {
val spark = Spark Session
.builder ()
.master ("local")[[[[]")
.appName ("teal")
.getOrCreate ()
import spark.implicits._
val df = spark.readStream
.format ("kafka")
//.setMaster("local[[[[
]")
.option ("kafka.bootstrap.servers", "127.0.0.1:9090")
.option ("subscribe", "test")
.Burden()
df.selectExpr ("CAST (key AS STRING)", "CAST (value AS STRING)")
.as[(String, String)]
val query = df.writeStream
.outputMode ("complete")
.format ("console")
.Begin()
}

######################################## ####### ## ############### "

Problem is: Exception in thread "main" org.apache.spark.sql.AnalysisException: The data source could not be found: kafka. Deploy the application according to the staging section of the Structured Streaming + Kafka Integration Guide.
at org.apache.spark.sql.execution.datasources.DataSource $ .lookupDataSource (DataSource.scala: 652)
at org.apache.spark.sql.streaming.DataStreamReader.load (DataStreamReader.scala: 161)

java – Problem Solving for Consumer Producer with JDBI, MySQL, HikariCP

The app is assuming to solve the producer-consumer problem. It would be great to have feedback on the overall design, testability, and general guidance for further improvement. I have doubts about choosing the right approach when testing a temporary database failure.

@ Slf4j
public class DataSource {

private static final string CONFIG_FILE = "src / main / resources / db / db.properties";
private static HikariConfig config = new HikariConfig (CONFIG_FILE);

private static HikariDataSource ds;

static{
To attempt {
ds = new HikariDataSource (config);
} catch (CJCommunicationsException | HikariPool.PoolInitializationException e) {
log.info (e.getMessage ());
}
}

static class holder {
static DataSource INSTANCE = new DataSource ();
}

private DataSource () {}

public static DataSource getInstance () {
return Holder.INSTANCE;
}

public static Connection getConnection () triggers SQLException {.
return ds.getConnection ();
}

public static HikariDataSource getDs () {
Return ds;
}
}

Quit Google+ for personal (personal) accounts on April 2, 2019

This is a discussion about Quit Google+ for personal (personal) accounts on April 2, 2019 within the Search Engine optimization Forums, part of the Internet Marketing category; Shut down Google+ for private (personal) accounts on April 2, 2019 https: //support.google.com/plus/answ…=&&& authuser = 0 …

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Steps to Get Your Windows PC Ready to Download McAfee Consumer Products – Everything Else

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mcafee.com/activate- McAfee Antivirus is a trusted antivirus. It has millions of users around the world. As you know, if you want to install it on your computer. Then you have to buy it. There are different methods to buy it. You can buy it online or offline. Once you've purchased it, you'll need to install it in your PC for protection. In this article, we'll try to understand how to download McAfee using a CD. You can also visit McAfee support if you want to learn more about McAfee.

Required system configuration to install McAfeecafe.com/activate

You can install McAfee Antivirus on your computer. To do this you need to have some required settings in your PC. Below is the necessary configuration:

Required Windows version

• Microsoft Windows 10 (32-bit and 6-bit)
• Microsoft Windows 8, 8.1 (32-bit and 62-bit)
• Windows 7 with Service Pack 1 (32-bit and 62-bit)

Minimal hard drive

• The minimum hard disk space should be 500 MB

Required internet connection

• A high speed internet connection is mandatory.

Browsers that support McAfee and protect against phishing

• Google Chrome web browser
• Mozilla Firefox web browser
• Microsoft EDGE
• Microsoft Internet Explorer

A CD / DVD-ROM

Before installing McAfee Antivirus-mcafee.com/activate, you must have some

If you want to install McAfee on your computer, you'll need to take a few steps. You must follow some instructions if you want a clean installation.

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linux – Kafka consumer: Reset offset for partition xxxx1-0 to offset 25143. Every time I start it

Topic-A:

o.a.k.c.c.i.ConsumerCoordinator - [Consumer clientId=consumer-1, groupId=group-5] Cancel previously assigned partitions []
o.a.k.c.c.i.AbstractCoordinator - [Consumer clientId=consumer-1, groupId=group-5] (Re) accession group
o.a.k.c.c.i.AbstractCoordinator - [Consumer clientId=consumer-1, groupId=group-5] Successful group with Generation 1
o.a.k.c.c.i.ConsumerCoordinator - [Consumer clientId=consumer-1, groupId=group-5] Set newly allocated partitions [A1-0]
o.a.k.c.consumer.internals.Fetcher - [Consumer clientId=consumer-1, groupId=group-5] Reset offset for partition A1-0 to offset 25143.

last message:

o.a.k.c.consumer.internals.Fetcher - [Consumer clientId=consumer-1, groupId=group-5] Reset offset for partition A1-0 to offset 25143.

This causes me to reset the offset every time I start. Suppose I run at number 25200, then I turn it off. The offset will be reset to 25143 on the next boot.
but I want to continue with the last offset.

This is another tip, and this is the normal result I want:
Toptic wallet:

org.apache.kafka.clients.Metadata - Cluster ID: iQU30Fo1TViA2rkH9cxVYQ
o.a.k.c.c.i.AbstractCoordinator - [Consumer clientId=consumer-3, groupId=wallet-1] Discovered group coordinator localhost: 9092 (id: 2147483646 rack: null)
o.a.k.c.c.i.ConsumerCoordinator - [Consumer clientId=consumer-3, groupId=wallet-1] Cancel previously assigned partitions []
o.a.k.c.c.i.AbstractCoordinator - [Consumer clientId=consumer-3, groupId=wallet-1] (Re) accession group
o.a.k.c.c.i.AbstractCoordinator - [Consumer clientId=consumer-3, groupId=wallet-1] Did the group succeed with Generation 13
o.a.k.c.c.i.ConsumerCoordinator - [Consumer clientId=consumer-3, groupId=wallet-1] Set newly allocated partitions [blockaddresscomplete3-0]

How should I stop Toptic-A?

Hotshoe Flash – Will external consumer flashes be unusable?

I'm currently spending a lot of time on flashes, and it seems to me that the manufacturer of cameras and flashguns is finding it increasingly difficult to derive value from an external flash.

I have an old flash unit with a guide number of 40, whose fixed angle is sufficient for f = 35 mm, so is advertised with a guide number of 40. There is an optional zoom head with its own guide number tables with 50 at f = 70 mm, 53 at f = 100 mm and 70 at f = 200 mm.

Now I come to an old flash with built-in zoom reflector that covers a range of f = 24mm to f = 100mm (basically, pull it out for a longer range). This is advertised with a guide number of 35. If you use the Sliderule style calculator on the back of the unit, you will notice that this guide number is f = 50mm. At f = 100mm it would have about 44, at f = 24mm (zoom head not extended at all) about 26. Ok, the indication at f = 50mm seems to be a certain compromise, even if the fixed flash flashes always covers a wider angle than this (but certainly not 24mm).

Now I look at the current offers of equal Manufacturer and you can not even find out the guide number at all. They indicate a guide number of 36, which is so small in the small print (f = 105 mm) that several traders indicate that this is the guide number at f = 50 mm. So, what does the leaflet say? I mean, apart from "we do everything automatically, do not bother". Look at Manual The indication of the flash power indicates that you can reduce up to M / 128. Consult a flash meter for the required reduction.

Come back?

Each has its own diameter system for comparison and reuse. While this spread began in analogue times, digital development has made it worse. I would expect third-party flash manufacturers to produce multi-standard flash units, but you need to buy your flash for each camera manufacturer (and sometimes for the type). The adapter system SCA3000 is on its way.

Now one of the main points of an external flash is possible compose a scene that mostly means the external flash is Not the sole responsible light source. Consequently, any automatism for determining its strength will turn out to be problematic, considering the things for which it is not responsible.

My impression is that "modern" flashes are weak and manufacturers do not even tell you As they are weak. If a flash is the only light in a scene and a direct light (which makes automatic zooming even more desirable), that's fine, and modern sensors allow you to shoot with higher ISO values ​​without much damage.

But as a competing light source, it has to oppose the sun in the back light (at worst). And you can not increase the ISO.

My impression is that the external flash units of consumers are moving in one direction in which they offer little over built-in camera flashes (short a tiltable / tiltable head), which would make them fake.

Am I wrong with this impression?