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As shown by the test results, the new Intel processors in the mid-price category in terms of performance have a noticeable superiority over their predecessors. With good multi-threaded program optimization, AMD chips with a large number of physical computing units can sometimes offer serious resistance. However, we must admit that this is an ideal case when all processor cores are used as efficiently as possible. Unfortunately, this is not often encountered in real applications.

In games, new Intel solutions are unconditionally superior. As we could see earlier, the Sandy Bridge microarchitecture copes well with such loads, and the gap between both predecessors and competitor's models is maximum here. Using motherboards based on Intel chipsets with the ICH8R / ICH9R / ICH10R south bridge , in our opinion, it is optimal to organize four terabyte disks as follows.

And for more reliable storage of important data, we will combine the second half of the volume of these disks into a RAID 5 array . We get both a super-fast 2 TB system disk and a reliable and capacious 1.5 TB "archive" volume. It is in this configuration of two arrays that we created with default values \u200b\u200bthat we will conduct our further testing. Improving the performance of a disk subsystem is a complex issue. The increase in computing power of modern processors has led to the fact that there is a clear imbalance between the capabilities of hard drives and the needs of processors.

At the same time, neither expensive SCSI disks, nor even IDE disks can save you. However, if the capabilities of one disk are not enough, then maybe the presence of several disks will partially solve this problem? In addition, is it possible, using multiple hard drives, to improve not only performance, but also data storage reliability, so that the failure of one of the drives does not lead to information loss?

This very approach was proposed back in 1987 by American researchers Patterson, Gibson and Katz from the University of California, Berkeley. Using the charges on Intel chipsets with the southern ICH8R / ICH9R / ICH10R bridge , four terabyte disks are optimal, in our opinion, to be organized as follows. And for more reliable storage of important data to us, the second half of these discs we combine into the RAID 5 array .

We also get a superfast system disk for 2 TB, and reliable and capacious "archive" volume by 1.5 TB. It is in such a configuration of two arrays we created with the default values, we will hold our further testing. In the calculation of the insulation thickness, the climate parameters are taken into account, based on the indicators under the abbreviation of the HSOP . It shows how much degrees and for how many days is necessary with the help of heating to increase the temperature outside the window to comfortable + 20 ° C inside the house. It is calculated as the difference between the inner temperature (+ 20 ° C) and the average for the heating period multiplied by the duration of this period in days. Two or more hard drives are combined into one by sequential merging and volume summing.

If we take two 500GB disks and create from them RAID-0, the operating system will treat this as one terabyte disk. Whereas if the database is located on one disk, the hard disk itself will perform read / write tasks by different users sequentially. RAID-0 will allow reading / writing in parallel. As a result, the more disks in the array RAID-0, the faster the array itself runs. The dependence is directly proportional - the speed increases by a factor of N, where N is the number of disks in the array.

These Intel Core i3 processors differ from others with good performance. This was largely achieved by specialists by lowering the heat release rate. The connector type in the model is of the "Socket" type.

The clock frequency of the device is at around 3500 MHz. The cache memory is the same as in other models. The processor core is installed in the "Bridge" series.

The speed of buffered reading in 3-5 GB / s is the values \u200b\u200bof one order with a bandwidth of system memory in a PC type of our test. The DMI bus, in which the southern bridge of Intel chipsets communicates with the system, has a much lower potential equal to the first generation PCI Express X4 tire (i.e. 1 GB / s in one direction). The second useful output from this diagram is for RAID arrays the data rate over the bus from the host to drives increases conditionally in proportion to the number of disks in the array. And for RAID 0, for example, at times exceeds the rate of data exchange with solitary SSD on the SATA bus.

Further on the list - the Intel Turbomode feature, which appeared in the Intel Core i5 and Core i7 processors, is known as "Turbo Boost". There are several parameters here to set limits to increase the performance of Intel Turbo Boost technology, such as the number of active nuclei, expected voltages, expected power consumption and processor temperature. The buffered read speed of 3-5 GB / s is on the same order of magnitude as the system memory bandwidth in a PC like our test. The second useful conclusion from this diagram is that for RAID arrays , the speed of data transfer over the bus from the host to the drives increases in proportion to the number of disks in the array.

And for RAID 0, for example, it is several times faster than the speed of data exchange with a single SSD on the SATA bus. When testing the Core i5-8400, we came across situations when this processor did not "fit" into the allotted limits for power consumption and heat dissipation and dropped its frequency below the nominal values. With the Core i3-8350K, such situations do not arise.

Its consumption never exceeds its allotted 91 W, thanks to which it operates at a constant 4.0 GHz frequency even during periods of maximum load. Accordingly, the use of a function that was useful for six-core processors cannot give any additional effect to the Core i3-8350K. The new Pentiums are on average 20% more productive than the CPUs of the same name for LGA1156 and practically compete on an equal footing with the Core i3 on the Clarkdale core, which are much more expensive.

Simplification of the functional part of these chips did not affect their speed performance too much. Therefore, these models can be fully recommended for creating universal systems and gaming platforms. In turn, the second generation Core i3 has significantly accelerated.

Well, in games, they sometimes look preferable to the quad-core AMD Phenom II X4. Considering that these processors have retained the functionality of older models, they may be interesting for creating both mid-level gaming PCs and powerful multimedia systems. Many mistakenly believe that to increase the performance of the computer, it is necessary to drive first of all the processor and the higher overclocking, the better the increase in the FPS. Although it is partly true and the frequency affects the performance of your computer very much, it also depends on the speed of RAM, as well as from the frequency of the video recorder and its memory.

On how to overclock the video card, we have already told in a separate article. Now it's time to pay attention to the frequency of RAM. Competent overclocking your RAM will allow significant Increase productivity. The beauty of the RAM acceleration is also in that, in contrast to or processor, higher frequencies and voltage of memory do not lead to the allocation of a very large amount of heat. Yes, the memory is still heating, but this heat dissipation does not matter any comparison with the heat generation of the overclocked processor or the video card.

The main function of a RAID array is not to increase the capacity of the disk subsystem , but to ensure the reliability of data safety and increase performance. For servers, in addition, a requirement is put forward for uninterrupted operation, even in the event of a failure of one of the drives. Continuity of operation is ensured by hot swapping, that is, removing the faulty SCSI disk and installing a new one without turning off the power. Because the disk subsystem continues to function with one failed drive , hot swapping provides user-transparent recovery.

However, the transmission speed and access speed with one non-working disk is noticeably reduced due to the fact that the controller must recover data from redundant information. True, there is an exception to this rule - RAID systems of levels 2, 3, 4 start working faster when a drive with redundant information fails! This is natural, since in this case the level "on the fly" changes to zero, which has excellent speed characteristics. Many people love this Intel Core i3 CPU 4150 processor for its high clock speed. All this allows owners to play a variety of modern games.

How Many Seconds In 2 Hours And 20 Minutes Additionally, this makes it possible to work with different programs. The quality of this model will be appreciated by people who work, for example, with video editors. Among other things, it should be noted a good TDP power.

The core in the processor is used by the "Nasvel" class. The cost of this device on the market is approximately 9600 rubles. This Intel Core i processor is capable of supporting many graphics cards. At the same time, it works absolutely silently and at high speed.

Separately, mention should be made of the new energy-saving system. The kernels are installed in the "Bridge" series. At the same time, the TDP power is at around 55 W. This model will cost about 9000 rubles on the market.

The internal clock frequency is at around 3700 MHz. Additionally, it should be noted that this dual-core processor has a good amount of cache memory. Integrated graphics in this model are provided by the manufacturer.

Among other things, it should be noted a good anti-virus protection. The mental balance of the parents depends on how the child grows and develops. To control physical development in infancy, mommy needs to measure the baby every month, paying special attention to the increase in height and weight.

If the values ​​obtained correspond to the table standards, then the child is growing healthy and there is no particular reason for concern. The RAID5 and RAID0 combination, partially correcting the main disadvantage of RAID5 - low data recording speed due to the parallel use of several such arrays. The total capacity of the array decreases to the container of two, but, unlike RAID6, this array transfers the failure of only one disk, and the minimum required number of disks to create the RAID50 array is 6. Along with the RAID10, this is the most recommended RAID level for use in Annexes where high performance is required in combination with acceptable reliability. Our expectations of productivity growth were high, but realistic.

Intel Nehalem architecture today has no equal performance on the tact; We expected it would be nice to scale with the addition of every megahertz to the clock frequency. Of course, we do not recommend going to such a step if you want to save low power consumption in idle mode. Comfortable accommodation in the house provides for the creation of conditions for maintaining the optimal air temperature especially in winter. In the construction of the house it is very important to competently pick up the insulation and calculate its thickness.

Any construction material Whether it is brick, concrete or foam block has its own thermal conductivity and heat resistance. Under thermal conductivity understand the ability of building materials to carry out heat. This value is defined in the laboratory conditions, and the data obtained are given by the manufacturer on the package or in special tables. Heat resistance - the value of the reverse thermal conductivity. That material that perfectly carries out heat, respectively, has low heat resistance. Curiously, the HD Tach RW 3.0 low-level test, which uses access to the drive bypassing the file system, showed values \u200b\u200bof 217 and 165 MB / s for these two parameters, respectively .

True, enabling write caching (WC \u003d yes in the diagrams) by means of Windows slightly slows down the sequential write and read speed, but it is not so critical that it could be considered unacceptable. Moving down the conventional scale of differentiation of current Intel processors, Core i3 is followed by Pentium chips. With the advent of the Core architecture, without exaggeration, the legendary brand was used to refer to reasonably affordable CPUs with a traditionally good price / performance ratio. The modernization of this line has been asking for a long time. Pentium on the Clarkdale core for the LGA1156 socket have not received significant distribution. The market situation at the time of the release of this platform developed in such a way that it was primarily positioned by Intel as a solution for mid-range and high-end systems.

Therefore, even after the expansion of the initial range of processors, the minimum cost of an admission ticket here remained quite high. The most affordable Pentium G6950 has a retail price of about $ 100, which is a bit expensive for an entry-level PC. It is not difficult to assume that Pentium for LGA1156, combining two crystals , has a higher cost price. Therefore, it is quite difficult to seriously reduce the price of these processors. In addition, in this case we are talking about budget chips of mass production. And motherboards cheaper than $ for LGA1156 actually appeared only after the announcement of Sandy Bridge.

The current line of processors consists of four models. The younger Core i with a clock speed of 3.1 GHz is offered for $ 117. Intel also envisioned a low-cost version of the i3-2100T with a 35W TDP. Typically, CPU power consumption can be reduced by lowering the operating clock frequency and supply voltage. On motherboards that allow the user to independently downlock and reduce the voltage below the recommended values, it is often possible to achieve similar results.

But in the event that this is not possible, the purchase of energy efficient models will be justified. Core i3-2100T operates at 2.5 GHz, and the frequency of the graphics unit has been reduced from 850 MHz to 650 MHz, while it can dynamically increase to 1.1 GHz. The core in the processor is installed of the Hasvel class. It should also be noted a reliable protection system.

Which Sql Query Must Have A Group By Clause When Used With Said Function

The GROUP BY clause groups the selected rows based on identical values in a column or expression. This clause is typically used with aggregate functions to generate a single result row for each set of unique values in a set of columns or expressions. Hence a window provides another opportunity to perform grouping and ordering operations in addition to a query's GROUP BY and ORDER BY clauses. However, any computation involving a window function's result – for example, using it in a predicate — will require a more complex statement construction. Typically that construction will require a derived table to compute the window function result, with the derived table's outer SELECT block containing the desired WHERE clause predicates. A window's partition can consist of the entire input, a single row, or something in between.

The advantage of a 'window' construct is that the rows within the partition can then be sorted to support the additional expressive power provided by window functions. Knowing how to use a SQLGROUP BY statement whenever you have aggregate functions is essential. In most cases, when you need an aggregate function, you must add aGROUP BY clause in your query too.

The first must contain a distinct first name of the employee and the second – the number of times this name is encountered in our database. With aggregate analytic functions, the OVER clause is appended to the aggregate function call; the function call syntax remains otherwise unchanged. Like their aggregate function counterparts, these analytic functions perform aggregations, but specifically over the relevant window frame for each row. The result data types of these analytic functions are the same as their aggregate function counterparts. In this article, Toptal Freelance SQL Developer Neal Barnett explains the benefits of SQL functions, describes when you'd use them, and gives you real examples to help with the concepts.

MySQL queries are SQL functions that help us to access a particular set of records from a database table. We can request any information or data from the database using the clauses or, let's say, SQL statements. A window function performs a calculation across a set of table rows that are somehow related to the current row. This is comparable to the type of calculation that can be done with an aggregate function. But unlike regular aggregate functions, use of a window function does not cause rows to become grouped into a single output row — the rows retain their separate identities. Behind the scenes, the window function is able to access more than just the current row of the query result.

Note that the ORDER BY specification makes no distinction between aggregate and non-aggregate rows of the result set. For instance, you might wish to list sales figures in declining order, but still have the subtotals at the end of each group. Simply ordering sales figures in descending sequence will not be sufficient, since that will place the subtotals at the start of each group.

Therefore, it is essential that the columns in the ORDER BY clause include columns that differentiate aggregate from non-aggregate columns. This requirement means that queries using ORDER BY along with aggregation extensions to GROUP BY will generally need to use one or more of the GROUPING functions. The CUBE, ROLLUP, and GROUPING SETS extensions to SQL make querying and reporting easier and faster. CUBE, ROLLUP, and grouping sets produce a single result set that is equivalent to a UNION ALL of differently grouped rows. ROLLUP calculates aggregations such as SUM, COUNT, MAX, MIN, and AVG at increasing levels of aggregation, from the most detailed up to a grand total.

CUBE is an extension similar to ROLLUP, enabling a single statement to calculate all possible combinations of aggregations. The CUBE, ROLLUP, and the GROUPING SETS extension lets you specify just the groupings needed in the GROUP BY clause. This allows efficient analysis across multiple dimensions without performing a CUBE operation. Computing a CUBE creates a heavy processing load, so replacing cubes with grouping sets can significantly increase performance. ROLLUP is an extension of the GROUP BY clause that creates a group for each of the column expressions.

Additionally, it "rolls up" those results in subtotals followed by a grand total. Under the hood, the ROLLUP function moves from right to left decreasing the number of column expressions that it creates groups and aggregations on. Since the column order affects the ROLLUP output, it can also affect the number of rows returned in the result set. The GROUP BY clause is often used in SQL statements which retrieve numerical data. It is commonly used with SQL functions like COUNT, SUM, AVG, MAX and MIN and is used mainly to aggregate data.

Data aggregation allows values from multiple rows to be grouped together to form a single row. The first table shows the marks scored by two students in a number of different subjects. The second table shows the average marks of each student. Still yields a single row in the result, with the values of 0 and NULL, respectively, for the two aggregate functions, since there are no Canadian players in the database taller than 200cm.

Here, the information from a table that does not satisfy the conditions is not used. So, by SQL statements, functions, operators and keywords in combination to SQL clauses makes the info access proper and manageable to deal with different tables in a database. To find the GROUP BY level of a particular row, a query must return GROUPING function information for each of the GROUP BY columns.

If we do this using the GROUPING function, every GROUP BY column requires another column using the GROUPING function. For instance, a four-column GROUP BY clause needs to be analyzed with four GROUPING functions. This is inconvenient to write in SQL and increases the number of columns required in the query.

When you want to store the query result sets in tables, as with materialized views, the extra columns waste storage space. A simple GROUP BY clause consists of a list of one or more columns or expressions that define the sets of rows that aggregations are to be performed on. A change in the value of any of the GROUP BY columns or expressions triggers a new set of rows to be aggregated. The OVER clause is what specifies a window function and must always be included in the statement.

The Group by clause is often used to arrange identical duplicate data into groups with a select statement to group the result-set by one or more columns. This clause works with the select specific list of items, and we can use HAVING, and ORDER BY clauses. Group by clause always works with an aggregate function like MAX, MIN, SUM, AVG, COUNT. Window functions are permitted only in the SELECT list and the ORDER BY clause of the query. They are forbidden elsewhere, such as in GROUP BY, HAVING and WHERE clauses. This is because they logically execute after the processing of those clauses.

Also, window functions execute after regular aggregate functions. This means it is valid to include an aggregate function call in the arguments of a window function, but not vice versa. Produced by the query's FROM clause as filtered by its WHERE, GROUP BY, and HAVING clauses if any. For example, a row removed because it does not meet the WHERE condition is not seen by any window function. A window function call always contains an OVER clause following the window function's name and argument. This is what syntactically distinguishes it from a regular function or aggregate function.

The OVER clause determines exactly how the rows of the query are split up for processing by the window function. The PARTITION BY list within OVER specifies dividing the rows into groups, or partitions, that share the same values of the PARTITION BY expression. For each row, the window function is computed across the rows that fall into the same partition as the current row. Expression_n Expressions that are not encapsulated within the MAX function and must be included in the GROUP BY clause at the end of the SQL statement.

Which Sql Query Must Have A Group By Clause When Used With Said Function Aggregate_expression This is the column or expression from which the maximum value will be returned. Tables The tables that you wish to retrieve records from. There must be at least one table listed in the FROM clause. These are conditions that must be met for the records to be selected.

It's a mistake is to preface each of the two statements with "Similar to the WHERE clause...". This clause is generally used with aggregate functions that allow grouping the query result rows by multiple columns. The aggregate functions are COUNT, MAX, MIN, SUM, AVG, etc. FILTER is a modifier used on an aggregate function to limit the values used in an aggregation.

All the columns in the select statement that aren't aggregated should be specified in a GROUP BY clause in the query. The HAVING clause in a SELECT specifies a condition to apply within a group or aggregate. In other words, HAVING filters rows after the aggregation of the GROUP BY clause has been applied. Since HAVING is evaluated after GROUP BY, it can only reference expressions constructed from grouping keys, aggregate expressions, and constants. (These are the same rules that apply to expressions in the SELECT clause of a GROUP BY query.) A HAVING clause must come after any GROUP BY clause and before any ORDER BY clause.

Results from a HAVING clause represent groupings or aggregations of original rows, whereas results from a WHERE clause are individual original rows. While this is a quick introduction to SQL window functions, hopefully it will spark your interest to see all that they can do. They always contain the OVER clause, and may contain PARTITION BY, ORDER BY, and a host of aggregating (SUM, COUNT, etc.) and other positional functions . We also learned about window frames and how they encapsulate sections of data. On the surface, the addition of the GROUP BY () appears harmless since the original statement was over the entire set of rows in the player table, restricted by the query's WHERE clause. This is an important distinction in the semantics of the SQL language – and it makes a difference in how one would write an application program that executes such a query.

This blog provides an overview of MySQL window functions. A window function performs an aggregate-like operation on a set of query rows. However, whereas an aggregate operation groups query rows into a single result row, a window function produces a result for each query row.

Each grouping set defines a set of columns for which an aggregate result is computed. The final result set is the set of distinct rows from the individual grouping column specifications in the grouping sets. GROUPING SETS syntax can be defined over simple column sets or CUBEs or ROLLUPs.

In effect, CUBE and ROLLUP are simply short forms for specific varieties of GROUPING SETS. The GROUPING function is not only useful for identifying NULLs, it also enables sorting subtotal rows and filtering results. In Example 20-8, you retrieve a subset of the subtotals created by a CUBE and none of the base-level aggregations. The HAVING clause constrains columns that use GROUPING functions. In this, the channel_desc value is determined with a DECODE function that contains a GROUPING function. The GROUPING function returns a 1 if a row value is an aggregate created by ROLLUP or CUBE, otherwise it returns a 0.

The DECODE function then operates on the GROUPING function's results. It returns the text "All Channels" if it receives a 1 and the channel_desc value from the database if it receives a 0. Values from the database will be either a real value such as "Internet" or a stored NULL. The second column specification, displaying country_id, works the same way. CUBE is typically most suitable in queries that use columns from multiple dimensions rather than columns representing different levels of a single dimension. For instance, a commonly requested cross-tabulation might need subtotals for all the combinations of month, state, and product.

These are three independent dimensions, and analysis of all possible subtotal combinations is commonplace. Subtotals such as profit by day of month summed across year would be unnecessary in most analyses. Use theSQL GROUP BYClause is to consolidate like values into a single row. The group by returns a single row from one or more within the query having the same column values. Its main purpose is this work alongside functions, such as SUM or COUNT, and provide a means to summarize values. This statement will return an error because you cannot use aggregate functions in a WHERE clause.

WHERE is used with GROUP BY when you want to filter rows before grouping them. The SUM() function returns the total value of all non-null values in a specified column. Since this is a mathematical process, it cannot be used on string values such as the CHAR, VARCHAR, and NVARCHAR data types. When used with a GROUP BY clause, the SUM() function will return the total for each category in the specified table.

Sorting takes place once the database has the entire result set ready . Once we have that, the database can now sort the result set using columns, selected aliases, or aggregation functions, even if they aren't part of the selected data. The only exception is when using the DISTINCT keyword, which prevents sorting by a non-selected column, as in that case the result set's order will be undefined.

The tables specified in the FROM clause , will be evaluated first, to determine the entire working set which is relevant for the query. After you get the result of your query—i.e., after the WHERE clause and any standard aggregation, window functions will act on the remaining rows and get you what you want. The WHERE clause specifies the criteria which individual records must meet to be selected by a query. The HAVING clause cannot be used without the GROUP BY clause. CUBE generates the GROUP BY aggregate rows, plus superaggregate rows for each unique combination of expressions in the column list.

The order of the columns specified in CUBE() has no effect. An analytic function computes values over a group of rows and returns a single result for each row. This is different from an aggregate function, which returns a single result for a group of rows.

Oracle Database can specify hierarchical cubes in a simple and efficient SQL query. These hierarchical cubes represent the logical cubes referred to in many OLAP products. By using concatenated rollup , you can generate all the aggregations needed by a hierarchical cube. Answering multidimensional questions often involves accessing and querying huge quantities of data, sometimes in millions of rows.

Because the flood of detailed data generated by large organizations cannot be interpreted at the lowest level, aggregated views of the information are essential. Aggregations, such as sums and counts, across many dimensions are vital to multidimensional analyses. Therefore, analytical tasks require convenient and efficient data aggregation. Adding a HAVING clause after your GROUP BY clause requires that you include any special conditions in both clauses. If the SELECT statement contains an expression, then it follows suit that the GROUP BY and HAVING clauses must contain matching expressions. It is similar in nature to the "GROUP BY with an EXCEPTION" sample from above.