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dieses Buch zu haben, aber nie zu überprüfen, Ziel ist eine Art von Unsinn. Sie müssen es auch nur einige überprüfen. Lesung von wenigen ist wirklich besser als nichts. Sie können ab der äußerst zufriedenstellend Zeit mit dem Lesen zu schätzen wissen. In dem Moment, wo man tatsächlich die Details aus dieser Veröffentlichung erforderlich filtern könnte. Das wird so hilfreich, wenn Sie tatsächlich genau verstehen, was eigentlich diese Veröffentlichung bietet. So finden Sie Ihr auf Mittel, um zu sehen, wie Sie Ihre Wahl in Bezug auf das neue Leben innerhalb des Buches.
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Erkennen Sie, was nur die Vorteile der Analyse sind? Vor gehen über in Bezug auf , werden wir Sie zuerst fragen. Was bekommen Sie nach dem Auschecken? Was bekommen Sie, nachdem ein Buch zu lesen enden? Genau das, was ist Ihr Gefühl? Nun, zahlreiche Bedenken wir sicherlich äußern Sie, die erstaunliche Veröffentlichung Enthusiasten, und auch die Besucher. Wir erwarten, dass Sie aufgrund der Tatsache, unglaublich sein, dass in diesem modernen Zeitalter, viele Menschen bevorzugen mit anderer Analyse zu sprechen. Aus diesem Grund sind die Gründe dafür, wie Führer sollten kultiviert werden sehr wichtig sind.
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Produktinformation
Format: Kindle Ausgabe
Dateigröße: 1944 KB
Seitenzahl der Print-Ausgabe: 212 Seiten
ISBN-Quelle für Seitenzahl: 1783989009
Verlag: Packt Publishing; Auflage: 1 (26. September 2016)
Verkauf durch: Amazon Media EU S.Ã r.l.
Sprache: Englisch
ASIN: B01LFAN8B6
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This book consists of a random selection of semi-literate re-hashes of the user manual and Wikipedia pages, along with a few code examples, most of which are broken.The authors jump from one topic to the next, never explaining anything in any real detail. For example, chapter one flits aimlessly from creating views, to creating cursors, to the GROUP BY clause to ‘complex’ topics such as subqueries and joins. This must be the only book on any database in which cursors are mentioned in the first few pages.Here are a few examples of how wretched the text is. For example, the section on cursors says:“It then uses a FETCH statement with the NEXT keyword to select the fifth row, and then another FETCHstatement with the PRIOR keyword to again select the fourth retrieved row.’To illustrate this, the authors provide the following:FETCH 4 FROM order_cur;Clearly, some code has been missed out, and nobody has noticed.In the section on JSON, several lines have again been missed out and/or replaced with the wrong code:“Let's create a normal table and insert data into it:CREATE TABLE product_info (id serial, product_name text, product_categorytext, price int);INSERT INTO product_info (product_name ,product_category , price)VALUES ('Chair', 'Furniture', 200);Now, since we have inserted the record in a normal way, we will change this to the JSONformat. We will use the row_to_json function:row_to_json-----------------------------------------------{"f1":"Chair","f2":"Furniture","f3":200}(1 row)â€I have no idea if the authors actually believe that typing ‘row_to_json’ would produce the result they claim: it obviously doesn’t. Nor does it work like this inside the obviously needed select statement. The next few lines are even more bizarre:“Similarly, we can output the array values as JSON with the help of the array_to_json function:CREATE TABLE product_info(id serial, product_category text, producttext[]);INSERT INTO product_info (product_category , product) VALUES('Stationary', '{"Pen","Pencil"}');â€Nothing is being output as JSON: instead, a new table is being created using JSON instead of text.Here’s another strange explanation:SELECT product, SUM(sale) AS "Total sales"FROM order_detailsGROUP BY product;‘In the select statement, we have sales where we applied the SUM function and the other fieldproduct is not part of SUM, we must use in the GROUP BY clause.’The authors are attempting to say “we must group on a field other than the one which we are aggregating: we use ‘group by’ on the product field and use the aggregate sum() function on the ‘sale’ field’â€.Here’s yet another example where the explanation is incomprehensible:“The HAVING clause is used to specify which individual group(s) is to be displayed, or in simple language we use theHAVING clause in order to filter the groups on the basis of an aggregate function condition.â€Compare this drivel with the clear explanation in the (free) user manual:“WHERE selects input rows before groups and aggregates are computed (thus, it controls which rows go into the aggregate computation), whereas HAVING selects group rows after groups and aggregates are computed.â€The section on transactions fails to explain either how isolation levels work or which ones PostgreSQL implements. The explanation of serializable isolation is particularly inadequate:‘As you saw in the preceding table, moving from the Read Uncommitted to Serializable level, the phenomena behavior is reducing.’In those cases where there isn’t a Wikipedia page as a source, the text descends into meaningless waffle. For example:“In a largely built database, there are cases where performance may not be up to the desiredexpectations. And, achieving more practical goals may spoil the purity of the design. Thesteps for the optimized design should be considered with the utmost priority before youeven consider any optimization.â€Clearly, neither of the authors has a proper grasp of English, and neither has enough experience of PostgreSQL to be able to write a useful book on the subject. Unbelievably, this garbage has been checked by over a dozen people. The book boasts a copy editor, two reviewers, a proof-reader, a technical editor, a content development editor, a production coordinator, a commissioning editor, an acquisition editor and a production coordinator. All of these people must be even more inept at their job than the authors or else asleep.
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