{"id":35400,"date":"2025-11-29T07:40:47","date_gmt":"2025-11-29T04:40:47","guid":{"rendered":"https:\/\/fatihsoysal.com\/blog\/?p=35400"},"modified":"2025-11-29T07:40:47","modified_gmt":"2025-11-29T04:40:47","slug":"java-8-stream-api-modern-veri-islemenin-gucu","status":"publish","type":"post","link":"https:\/\/fatihsoysal.com\/blog\/java-8-stream-api-modern-veri-islemenin-gucu\/","title":{"rendered":"Java 8 Stream API: Modern Veri \u0130\u015flemenin G\u00fcc\u00fc"},"content":{"rendered":"

<\/p>\n

Java 8 Stream API: Modern Veri \u0130\u015flemenin G\u00fcc\u00fc<\/h2>\n

Java 8 ile birlikte tan\u0131t\u0131lan Stream API, koleksiyonlar \u00fczerinde fonksiyonel stil operasyonlar ger\u00e7ekle\u015ftirme yetene\u011fi sunarak Java programlama dilinde veri i\u015flemeyi k\u00f6kten de\u011fi\u015ftirdi. Bu g\u00fc\u00e7l\u00fc API, daha okunabilir, daha az tekrarlayan (boilerplate) ve potansiyel olarak daha performansl\u0131 kod yazmam\u0131z\u0131 sa\u011flayan yeni bir paradigma getirdi. Geleneksel d\u00f6ng\u00fclerle (for, while) yap\u0131lan karma\u015f\u0131k ve i\u00e7 i\u00e7e ge\u00e7mi\u015f veri i\u015fleme g\u00f6revlerini, deklaratif ve ard\u0131\u015f\u0131k bir dizi i\u015flem olarak ifade etmemizi m\u00fcmk\u00fcn k\u0131lar.<\/p>\n

Stream API’nin temel amac\u0131, koleksiyonlardaki verileri bir dizi i\u015flemden ge\u00e7irmek i\u00e7in soyut bir aray\u00fcz sa\u011flamakt\u0131r. Bu i\u015flemler, veriyi filtrelemek, d\u00f6n\u00fc\u015ft\u00fcrmek, s\u0131ralamak veya \u00f6zetlemek gibi \u00e7e\u015fitli g\u00f6revleri i\u00e7erebilir. Stream’ler, bir veri kayna\u011f\u0131 (\u00f6rne\u011fin bir List<\/code>, Set<\/code>, Array veya I\/O kanal\u0131) \u00fczerinde \u00e7al\u0131\u015f\u0131r, bu verileri bir “i\u015flem hatt\u0131” (pipeline) boyunca ak\u0131t\u0131r ve sonunda bir sonu\u00e7 \u00fcretir. Bu makale, Java 8 Stream API’nin temel kavramlar\u0131n\u0131, kullan\u0131m\u0131n\u0131, avantajlar\u0131n\u0131 ve en iyi uygulamalar\u0131n\u0131 derinlemesine inceleyecektir.<\/p>\n

Temel Kavramlar ve Avantajlar\u0131<\/h2>\n

Java Stream API’yi anlamak i\u00e7in birka\u00e7 temel kavram\u0131 bilmek \u00f6nemlidir. Bu kavramlar, stream’lerin nas\u0131l \u00e7al\u0131\u015ft\u0131\u011f\u0131n\u0131 ve neden bu kadar g\u00fc\u00e7l\u00fc olduklar\u0131n\u0131 a\u00e7\u0131klar.<\/p>\n

Stream Nedir?<\/h3>\n

Stream, bir veri kayna\u011f\u0131 \u00fczerindeki elemanlar\u0131n ard\u0131\u015f\u0131k bir dizisidir ve bu elemanlar \u00fczerinde bir veya daha fazla i\u015flem ger\u00e7ekle\u015ftirilebilir. Bir stream, asl\u0131nda bir veri yap\u0131s\u0131 de\u011fildir; daha ziyade, bir veri kayna\u011f\u0131n\u0131 i\u015flemek i\u00e7in bir soyutlama katman\u0131d\u0131r. Stream’ler, elemanlar\u0131 depolamaz; bunun yerine, elemanlar\u0131 talep edildi\u011finde kaynaktan al\u0131r ve bir i\u015flem hatt\u0131ndan ge\u00e7irir. Bir stream, tek kullan\u0131ml\u0131kt\u0131r; bir terminal i\u015flem ger\u00e7ekle\u015ftirildikten sonra “t\u00fcketilir” ve tekrar kullan\u0131lamaz. Yeniden i\u015flem yapmak i\u00e7in yeni bir stream olu\u015fturulmas\u0131 gerekir.<\/p>\n

Lazy Evaluation (Tembel De\u011ferlendirme)<\/h3>\n

Stream API’nin en \u00f6nemli \u00f6zelliklerinden biri tembel de\u011ferlendirmedir. Bu, stream \u00fczerindeki ara i\u015flemlerin (intermediate operations) hemen y\u00fcr\u00fct\u00fclmedi\u011fi anlam\u0131na gelir. Bunun yerine, bu i\u015flemler bir i\u015flem hatt\u0131 olu\u015fturur ve yaln\u0131zca bir terminal i\u015flem \u00e7a\u011fr\u0131ld\u0131\u011f\u0131nda ger\u00e7ekten y\u00fcr\u00fct\u00fcl\u00fcrler. Bu yakla\u015f\u0131m, gereksiz hesaplamalar\u0131 \u00f6nleyerek performans\u0131 art\u0131rabilir. \u00d6rne\u011fin, bir milyon elemanl\u0131 bir listeden yaln\u0131zca ilk 10 eleman\u0131 almak istedi\u011finizde, stream t\u00fcm bir milyon eleman\u0131 i\u015flemek yerine, sadece gerekli olan 10 eleman\u0131 i\u015fleyecektir.<\/p>\n

Immutability (De\u011fi\u015fmezlik)<\/h3>\n

Stream’ler, veri kaynaklar\u0131n\u0131 de\u011fi\u015ftirmez. Bir stream i\u015flemi, orijinal koleksiyonu veya diziyi etkilemez; her zaman yeni bir sonu\u00e7 \u00fcretir. Bu, yan etkilerden ka\u00e7\u0131nmaya ve daha g\u00fcvenli, \u00f6ng\u00f6r\u00fclebilir kod yazmaya yard\u0131mc\u0131 olur.<\/p>\n

Non-Interfering (M\u00fcdahale Etmeme)<\/h3>\n

Stream i\u015flemleri, stream’in kayna\u011f\u0131n\u0131 i\u015flenirken de\u011fi\u015ftirmemelidir. Bu, \u00f6zellikle paralel stream’ler i\u00e7in \u00f6nemlidir, \u00e7\u00fcnk\u00fc birden fazla i\u015f par\u00e7ac\u0131\u011f\u0131n\u0131n ayn\u0131 anda kayna\u011f\u0131 de\u011fi\u015ftirmeye \u00e7al\u0131\u015fmas\u0131 \u00f6ng\u00f6r\u00fclemeyen sonu\u00e7lara yol a\u00e7abilir.<\/p>\n

Stream Ya\u015fam D\u00f6ng\u00fcs\u00fc: Kaynak, Ara \u0130\u015flemler, Terminal \u0130\u015flemler<\/h3>\n

Bir stream i\u015flem hatt\u0131 \u00fc\u00e7 ana b\u00f6l\u00fcmden olu\u015fur:
\n* Kaynak (Source):<\/strong> Stream’in verilerini ald\u0131\u011f\u0131 yerdir. Bu bir koleksiyon, dizi, I\/O kanal\u0131 veya ba\u015fka bir veri yap\u0131s\u0131 olabilir.
\n* Ara \u0130\u015flemler (Intermediate Operations):<\/strong> Bunlar, bir stream’i ba\u015fka bir stream’e d\u00f6n\u00fc\u015ft\u00fcren i\u015flemlerdir. Zincirlenebilirler ve tembel de\u011ferlendirilirler. \u00d6rnekler: filter()<\/code>, map()<\/code>, sorted()<\/code>, distinct()<\/code>, limit()<\/code>, skip()<\/code>.
\n* Terminal \u0130\u015flemler (Terminal Operations):<\/strong> Stream i\u015flem hatt\u0131n\u0131 ba\u015flatan ve bir nihai sonu\u00e7 \u00fcreten i\u015flemlerdir. Bu sonu\u00e7 bir de\u011fer (\u00f6rne\u011fin bir say\u0131), bir koleksiyon veya bir yan etki (side-effect) olabilir. Bir terminal i\u015flem \u00e7a\u011fr\u0131ld\u0131\u011f\u0131nda, stream t\u00fcketilir. \u00d6rnekler: forEach()<\/code>, collect()<\/code>, reduce()<\/code>, sum()<\/code>, count()<\/code>, min()<\/code>, max()<\/code>, anyMatch()<\/code>, allMatch()<\/code>, noneMatch()<\/code>, findFirst()<\/code>, findAny()<\/code>.<\/p>\n

Avantajlar\u0131<\/h3>\n

* Okunabilirlik ve Kod Azl\u0131\u011f\u0131:<\/strong> Karma\u015f\u0131k d\u00f6ng\u00fcler ve if-else bloklar\u0131 yerine, ak\u0131c\u0131 ve deklaratif bir tarzda veri i\u015fleme mant\u0131\u011f\u0131n\u0131 ifade etmeye olanak tan\u0131r.
\n* Paralel \u0130\u015flem Yetene\u011fi:<\/strong> Stream’ler, parallelStream()<\/code> y\u00f6ntemiyle kolayca paralel hale getirilebilir, bu da \u00e7ok \u00e7ekirdekli i\u015flemcilerde performans\u0131 art\u0131rabilir.
\n* Fonksiyonel Yakla\u015f\u0131m:<\/strong> Lambda ifadeleri ve metot referanslar\u0131 ile birlikte kullan\u0131larak fonksiyonel programlama prensiplerini Java’ya ta\u015f\u0131r.
\n* Daha Az Hata:<\/strong> De\u011fi\u015fmezlik ve yan etkilerden ka\u00e7\u0131nma prensipleri sayesinde daha az hata i\u00e7eren kod yaz\u0131lmas\u0131na yard\u0131mc\u0131 olur.<\/p>\n

Stream Olu\u015fturma<\/h2>\n

Stream API’nin ilk ad\u0131m\u0131, \u00fczerinde \u00e7al\u0131\u015f\u0131lacak bir stream olu\u015fturmakt\u0131r. Java, \u00e7e\u015fitli kaynaklardan stream olu\u015fturmak i\u00e7in birden fazla y\u00f6ntem sunar.<\/p>\n

Koleksiyonlardan<\/h3>\n

Java koleksiyonlar\u0131, stream()<\/code> metodunu do\u011frudan \u00e7a\u011f\u0131rarak bir stream olu\u015fturabilir.<\/p>\n

List isimler = Arrays.asList(\"Ali\", \"Ay\u015fe\", \"Mehmet\", \"Fatma\");\nStream isimStream = isimler.stream(); \/\/ List'ten stream<\/code><\/pre>\n
Set<\/code> ve Map<\/code> gibi di\u011fer koleksiyon t\u00fcrleri de benzer \u015fekilde stream olu\u015fturabilir:<\/p>\n
Set sayilar = new HashSet<>(Arrays.asList(1, 2, 3, 4, 5));\nStream sayiStream = sayilar.stream(); \/\/ Set'ten stream\n\nMap yaslar = new HashMap<>();\nyaslar.put(\"Ali\", 30);\nyaslar.put(\"Ay\u015fe\", 25);\nStream> entryStream = yaslar.entrySet().stream(); \/\/ Map entry'lerinden stream<\/code><\/pre>\n
Dizilerden<\/h3>\n
Diziler de kolayca stream’e d\u00f6n\u00fc\u015ft\u00fcr\u00fclebilir.<\/p>\n
String[] sehirler = {\"Ankara\", \"\u0130stanbul\", \"\u0130zmir\"};\nStream sehirStream = Arrays.stream(sehirler); \/\/ String dizisinden stream\n\nint[] intDizisi = {10, 20, 30};\nIntStream intStream = Arrays.stream(intDizisi); \/\/ Primitive int dizisinden IntStream<\/code><\/pre>\n
Ayr\u0131ca, Stream.of()<\/code> metodu ile do\u011frudan elemanlardan bir stream olu\u015fturabilirsiniz:<\/p>\n
Stream renkStream = Stream.of(\"K\u0131rm\u0131z\u0131\", \"Mavi\", \"Ye\u015fil\");\nStream tekSayilar = Stream.of(1, 3, 5, 7, 9);<\/code><\/pre>\n
Dosya I\/O’dan<\/h3>\n
java.nio.file.Files<\/code> s\u0131n\u0131f\u0131, dosya i\u00e7eriklerini sat\u0131r sat\u0131r okuyarak bir stream olu\u015fturmak i\u00e7in kullan\u0131labilir.<\/p>\n
import java.nio.file.Files;\nimport java.nio.file.Paths;\nimport java.io.IOException;\n\ntry {\n    Stream satirStream = Files.lines(Paths.get(\"dosya.txt\"));\n    \/\/ satirStream \u00fczerinde i\u015flemler yap\u0131labilir\n    satirStream.forEach(System.out::println);\n} catch (IOException e) {\n    e.printStackTrace();\n}<\/code><\/pre>\n
Di\u011fer Y\u00f6ntemler<\/h3>\n
*   Stream.builder()<\/code>:<\/strong> Elemanlar\u0131 manuel olarak ekleyerek bir stream olu\u015fturur.<\/p>\n
Stream.Builder builder = Stream.builder();\n    builder.add(\"Elma\").add(\"Armut\").add(\"Kiraz\");\n    Stream meyveStream = builder.build();<\/code><\/pre>\n
*   Stream.generate()<\/code>:<\/strong> Bir Supplier<\/code> kullanarak sonsuz bir stream olu\u015fturur. limit()<\/code> ile s\u0131n\u0131rland\u0131r\u0131lmal\u0131d\u0131r.<\/p>\n
Stream rastgeleSayilar = Stream.generate(Math::random).limit(5);\n    rastgeleSayilar.forEach(System.out::println);<\/code><\/pre>\n
*   Stream.iterate()<\/code>:<\/strong> Bir ba\u015flang\u0131\u00e7 de\u011feri ve bir UnaryOperator<\/code> kullanarak sonsuz bir stream olu\u015fturur. limit()<\/code> ile s\u0131n\u0131rland\u0131r\u0131lmal\u0131d\u0131r.<\/p>\n
Stream ciftSayilar = Stream.iterate(0, n -> n + 2).limit(10);\n    ciftSayilar.forEach(System.out::println); \/\/ 0, 2, 4, ..., 18<\/code><\/pre>\n
*   Primitive Stream’ler:<\/strong> IntStream<\/code>, LongStream<\/code>, DoubleStream<\/code> gibi ilkel tipler i\u00e7in optimize edilmi\u015f stream’ler de mevcuttur. Bu stream’ler, otomatik kutulama (autoboxing) maliyetinden ka\u00e7\u0131narak daha iyi performans sunar.<\/p>\n
IntStream.range(1, 5).forEach(System.out::println); \/\/ 1, 2, 3, 4 (5 dahil de\u011fil)\n    IntStream.rangeClosed(1, 5).forEach(System.out::println); \/\/ 1, 2, 3, 4, 5 (5 dahil)<\/code><\/pre>\n
Ara \u0130\u015flemler (Intermediate Operations)<\/h2>\n
Ara i\u015flemler, bir stream’i ba\u015fka bir stream’e d\u00f6n\u00fc\u015ft\u00fcren ve tembel de\u011ferlendirilen i\u015flemlerdir. Zincirlenebilirler ve bir terminal i\u015flem \u00e7a\u011fr\u0131lana kadar ger\u00e7ekte y\u00fcr\u00fct\u00fclmezler.<\/p>\n
Filtreleme (filter()<\/code>)<\/h3>\n
filter()<\/code> metodu, belirli bir ko\u015fulu kar\u015f\u0131layan elemanlar\u0131 stream’den ge\u00e7irir. Bir Predicate<\/code> (boolean d\u00f6nd\u00fcren fonksiyonel aray\u00fcz) al\u0131r.<\/p>\n
List kelimeler = Arrays.asList(\"elma\", \"armut\", \"kiraz\", \"\u00fcz\u00fcm\", \"erik\");\nList aIleBaslayanlar = kelimeler.stream()\n                                      .filter(s -> s.startsWith(\"a\"))\n                                      .collect(Collectors.toList()); \/\/ [elma, armut]<\/code><\/pre>\n
D\u00f6n\u00fc\u015ft\u00fcrme (Mapping) (map()<\/code>, flatMap()<\/code>)<\/h3>\n
*   map()<\/code>:<\/strong> Stream’deki her eleman\u0131 belirli bir fonksiyona g\u00f6re d\u00f6n\u00fc\u015ft\u00fcr\u00fcr ve yeni bir stream d\u00f6nd\u00fcr\u00fcr. Bir Function<\/code> al\u0131r.<\/p>\n
List sayilar = Arrays.asList(1, 2, 3, 4, 5);\n    List kareler = sayilar.stream()\n                                 .map(n -> n * n)\n                                 .collect(Collectors.toList()); \/\/ [1, 4, 9, 16, 25]<\/code><\/pre>\n
*   flatMap()<\/code>:<\/strong> \u0130\u00e7 i\u00e7e ge\u00e7mi\u015f koleksiyonlar\u0131 veya dizileri d\u00fczle\u015ftirmek i\u00e7in kullan\u0131l\u0131r. Her eleman\u0131 bir stream’e d\u00f6n\u00fc\u015ft\u00fcren bir Function<\/code> al\u0131r ve bu stream’leri tek bir stream’de birle\u015ftirir.<\/p>\n
List> listeler = Arrays.asList(\n        Arrays.asList(\"a\", \"b\"),\n        Arrays.asList(\"c\", \"d\")\n    );\n    List duzlestirilmisListe = listeler.stream()\n                                              .flatMap(Collection::stream)\n                                              .collect(Collectors.toList()); \/\/ [a, b, c, d]<\/code><\/pre>\n
S\u0131ralama (sorted()<\/code>)<\/h3>\n
sorted()<\/code> metodu, stream’deki elemanlar\u0131 do\u011fal s\u0131ralamalar\u0131na g\u00f6re veya belirtilen bir Comparator<\/code>‘a g\u00f6re s\u0131ralar.<\/p>\n
List meyveler = Arrays.asList(\"kiraz\", \"elma\", \"muz\", \"armut\");\nList siraliMeyveler = meyveler.stream()\n                                    .sorted() \/\/ Do\u011fal s\u0131ralama\n                                    .collect(Collectors.toList()); \/\/ [armut, elma, kiraz, muz]\n\nList uzunlugaGoreSirali = meyveler.stream()\n                                        .sorted(Comparator.comparingInt(String::length))\n                                        .collect(Collectors.toList()); \/\/ [muz, elma, armut, kiraz]<\/code><\/pre>\n
Benzersiz \u00d6\u011feler (distinct()<\/code>)<\/h3>\n
distinct()<\/code> metodu, stream’deki yinelenen elemanlar\u0131 kald\u0131r\u0131r ve yaln\u0131zca benzersiz elemanlar\u0131 i\u00e7eren bir stream d\u00f6nd\u00fcr\u00fcr. Elemanlar\u0131n equals()<\/code> ve hashCode()<\/code> metotlar\u0131na dayan\u0131r.<\/p>\n
List sayilar = Arrays.asList(1, 2, 2, 3, 4, 4, 5);\nList benzersizSayilar = sayilar.stream()\n                                       .distinct()\n                                       .collect(Collectors.toList()); \/\/ [1, 2, 3, 4, 5]<\/code><\/pre>\n
S\u0131n\u0131rland\u0131rma ve Atlama (limit()<\/code>, skip()<\/code>)<\/h3>\n
*   limit()<\/code>:<\/strong> Stream’deki eleman say\u0131s\u0131n\u0131 belirtilen maksimum say\u0131ya s\u0131n\u0131rlar.<\/p>\n
List ilkUcSayi = IntStream.rangeClosed(1, 10)\n                                     .limit(3)\n                                     .boxed() \/\/ IntStream'i Stream'a d\u00f6n\u00fc\u015ft\u00fcr\u00fcr\n                                     .collect(Collectors.toList()); \/\/ [1, 2, 3]<\/code><\/pre>\n
*   skip()<\/code>:<\/strong> Stream’in ba\u015f\u0131ndan belirtilen say\u0131da eleman\u0131 atlar.<\/p>\n
List sonYediSayi = IntStream.rangeClosed(1, 10)\n                                       .skip(3)\n                                       .boxed()\n                                       .collect(Collectors.toList()); \/\/ [4, 5, 6, 7, 8, 9, 10]<\/code><\/pre>\n
Peek (peek()<\/code>)<\/h3>\n
peek()<\/code> metodu, stream’deki her eleman \u00fczerinde bir yan etki (side-effect) ger\u00e7ekle\u015ftirmek i\u00e7in kullan\u0131l\u0131r. Genellikle hata ay\u0131klama (debugging) veya ara durumlar\u0131 g\u00f6zlemlemek i\u00e7in kullan\u0131l\u0131r. Stream’i de\u011fi\u015ftirmez ve yeni bir stream d\u00f6nd\u00fcr\u00fcr.<\/p>\n
List sonuc = Arrays.asList(\"a\", \"b\", \"c\").stream()\n                           .peek(e -> System.out.println(\"Filtrelemeden \u00f6nce: \" + e))\n                           .filter(e -> e.equals(\"b\"))\n                           .peek(e -> System.out.println(\"Filtrelemeden sonra: \" + e))\n                           .collect(Collectors.toList()); \/\/ Filtrelemeden \u00f6nce: a, Filtrelemeden \u00f6nce: b, Filtrelemeden sonra: b, Filtrelemeden \u00f6nce: c<\/code><\/pre>\n
Terminal \u0130\u015flemler (Terminal Operations)<\/h2>\n
Terminal i\u015flemler, stream i\u015flem hatt\u0131n\u0131 sonland\u0131r\u0131r ve bir sonu\u00e7 \u00fcretir. Bu sonu\u00e7 bir de\u011fer, bir koleksiyon veya bir yan etki olabilir. Bir terminal i\u015flem \u00e7a\u011fr\u0131ld\u0131\u011f\u0131nda, stream t\u00fcketilir ve tekrar kullan\u0131lamaz.<\/p>\n
Toplama (Reduction) (reduce()<\/code>)<\/h3>\n
reduce()<\/code> metodu, stream’deki t\u00fcm elemanlar\u0131 tek bir sonuca indirgemek i\u00e7in kullan\u0131l\u0131r. \u00dc\u00e7 farkl\u0131 a\u015f\u0131r\u0131 y\u00fcklenmi\u015f versiyonu vard\u0131r:
\n*   Optional reduce(BinaryOperator accumulator)<\/code>: Bir ba\u015flang\u0131\u00e7 de\u011feri olmadan.
\n*   T reduce(T identity, BinaryOperator accumulator)<\/code>: Bir ba\u015flang\u0131\u00e7 de\u011feri (identity) ile.
\n*   U reduce(U identity, BiFunction accumulator, BinaryOperator combiner)<\/code>: Paralel stream’ler i\u00e7in birle\u015ftirici (combiner) ile.<\/p>\n
List sayilar = Arrays.asList(1, 2, 3, 4, 5);\nOptional toplam = sayilar.stream().reduce(Integer::sum); \/\/ Optional[15]\n\nint carpim = sayilar.stream().reduce(1, (a, b) -> a * b); \/\/ 120\n\n\/\/ Primitive stream'lerde \u00f6zel reduction metotlar\u0131\nint toplamInt = IntStream.rangeClosed(1, 5).sum(); \/\/ 15\ndouble ortalama = IntStream.rangeClosed(1, 5).average().getAsDouble(); \/\/ 3.0<\/code><\/pre>\n
Koleksiyona D\u00f6n\u00fc\u015ft\u00fcrme (collect()<\/code>)<\/h3>\n
collect()<\/code> metodu, stream elemanlar\u0131n\u0131 bir Collector<\/code> kullanarak bir koleksiyona veya ba\u015fka bir veri yap\u0131s\u0131na toplar. java.util.stream.Collectors<\/code> s\u0131n\u0131f\u0131, bir\u00e7ok yayg\u0131n toplama i\u015flemi i\u00e7in haz\u0131r collector’lar sa\u011flar.
\n*   toList()<\/code>, toSet()<\/code>, toCollection()<\/code>:<\/strong> Elemanlar\u0131 bir List<\/code>, Set<\/code> veya belirli bir koleksiyon t\u00fcr\u00fcne toplar.<\/p>\n
List isimler = Arrays.asList(\"Ali\", \"Ay\u015fe\", \"Ali\", \"Zeynep\");\n    List liste = isimler.stream().collect(Collectors.toList()); \/\/ [Ali, Ay\u015fe, Ali, Zeynep]\n    Set set = isimler.stream().collect(Collectors.toSet());   \/\/ [Ali, Ay\u015fe, Zeynep] (s\u0131ra garanti de\u011fil)<\/code><\/pre>\n
*   toMap()<\/code>:<\/strong> Elemanlar\u0131 bir Map<\/code>‘e d\u00f6n\u00fc\u015ft\u00fcr\u00fcr. Anahtar ve de\u011fer fonksiyonlar\u0131 belirtilmelidir.<\/p>\n
List meyveler = Arrays.asList(\"elma\", \"armut\", \"kiraz\");\n    Map meyveUzunluklari = meyveler.stream()\n                                                  .collect(Collectors.toMap(\n                                                      Function.identity(), \/\/ Eleman\u0131n kendisi anahtar\n                                                      String::length      \/\/ Uzunlu\u011fu de\u011fer\n                                                  )); \/\/ {elma=4, armut=5, kiraz=5}<\/code><\/pre>\n
*   groupingBy()<\/code>:<\/strong> Elemanlar\u0131 belirli bir \u00f6zelli\u011fe g\u00f6re gruplar.<\/p>\n
Map> uzunlugaGoreGrupla = meyveler.stream()\n                                                           .collect(Collectors.groupingBy(String::length));\n    \/\/ {4=[elma], 5=[armut, kiraz]}<\/code><\/pre>\n
*   partitioningBy()<\/code>:<\/strong> Elemanlar\u0131 bir Predicate<\/code>‘e g\u00f6re iki gruba ay\u0131r\u0131r (true\/false).<\/p>\n
Map> ciftTekSayilar = IntStream.rangeClosed(1, 5)\n                                                         .boxed()\n                                                         .collect(Collectors.partitioningBy(n -> n % 2 == 0));\n    \/\/ {false=[1, 3, 5], true=[2, 4]}<\/code><\/pre>\n
*   joining()<\/code>:<\/strong> String elemanlar\u0131n\u0131 birle\u015ftirir.<\/p>\n
String birlesikMeyveler = meyveler.stream().collect(Collectors.joining(\", \")); \/\/ elma, armut, kiraz<\/code><\/pre>\n
*   \u00d6zetleme Collector’lar\u0131:<\/strong> counting()<\/code>, summingInt()<\/code>, averagingDouble()<\/code>, summarizingInt()<\/code> gibi metotlar.<\/p>\n
Long elemanSayisi = meyveler.stream().collect(Collectors.counting()); \/\/ 3\n    Integer toplamUzunluk = meyveler.stream().collect(Collectors.summingInt(String::length)); \/\/ 14\n    Double ortalamaUzunluk = meyveler.stream().collect(Collectors.averagingDouble(String::length)); \/\/ 4.666...<\/code><\/pre>\n
D\u00f6ng\u00fcleme (forEach()<\/code>, forEachOrdered()<\/code>)<\/h3>\n
forEach()<\/code> metodu, stream’deki her eleman \u00fczerinde bir yan etki ger\u00e7ekle\u015ftirmek i\u00e7in kullan\u0131l\u0131r. Bir Consumer<\/code> al\u0131r. forEachOrdered()<\/code> ise, paralel stream’lerde bile elemanlar\u0131n orijinal s\u0131ras\u0131n\u0131 korur.<\/p>\n
List isimler = Arrays.asList(\"Ali\", \"Ay\u015fe\", \"Mehmet\");\nisimler.stream().forEach(System.out::println); \/\/ Her ismi yeni sat\u0131ra yazd\u0131r\u0131r<\/code><\/pre>\n
E\u015fle\u015fme (Matching) (allMatch()<\/code>, anyMatch()<\/code>, noneMatch()<\/code>)<\/h3>\n
Bu metotlar, stream’deki elemanlar\u0131n belirli bir Predicate<\/code>‘i kar\u015f\u0131lay\u0131p kar\u015f\u0131lamad\u0131\u011f\u0131n\u0131 kontrol eder ve bir boolean<\/code> d\u00f6nd\u00fcr\u00fcr. K\u0131sa devre (short-circuiting) \u00f6zelli\u011fine sahiptirler.
\n*   allMatch()<\/code>:<\/strong> T\u00fcm elemanlar ko\u015fulu sa\u011fl\u0131yorsa true<\/code>.
\n*   anyMatch()<\/code>:<\/strong> Herhangi bir eleman ko\u015fulu sa\u011fl\u0131yorsa true<\/code>.
\n*   noneMatch()<\/code>:<\/strong> Hi\u00e7bir eleman ko\u015fulu sa\u011flam\u0131yorsa true<\/code>.<\/p>\n
List sayilar = Arrays.asList(2, 4, 6, 8);\nboolean hepsiCiftMi = sayilar.stream().allMatch(n -> n % 2 == 0); \/\/ true\nboolean tekSayiVarMi = sayilar.stream().anyMatch(n -> n % 2 != 0); \/\/ false\nboolean hicTekSayiYokMu = sayilar.stream().noneMatch(n -> n % 2 != 0); \/\/ true<\/code><\/pre>\n
Bulma (Finding) (findFirst()<\/code>, findAny()<\/code>)<\/h3>\n
Bu metotlar, stream’den bir eleman d\u00f6nd\u00fcr\u00fcr ve bir Optional<\/code> i\u00e7erisine sarar. K\u0131sa devre \u00f6zelli\u011fine sahiptirler.
\n*   findFirst()<\/code>:<\/strong> Stream’deki ilk eleman\u0131 d\u00f6nd\u00fcr\u00fcr (s\u0131ral\u0131 stream’lerde).
\n*   findAny()<\/code>:<\/strong> Stream’deki herhangi bir eleman\u0131 d\u00f6nd\u00fcr\u00fcr (paralel stream’lerde daha verimli olabilir).<\/p>\n
List meyveler = Arrays.asList(\"elma\", \"armut\", \"kiraz\");\nOptional ilkMeyve = meyveler.stream().findFirst(); \/\/ Optional[elma]\nOptional herhangiMeyve = meyveler.stream().findAny(); \/\/ Optional[elma] (s\u0131ral\u0131 stream'de genellikle ilk eleman)<\/code><\/pre>\n
Di\u011fer (toArray()<\/code>)<\/h3>\n
toArray()<\/code> metodu, stream elemanlar\u0131n\u0131 bir diziye d\u00f6n\u00fc\u015ft\u00fcr\u00fcr.<\/p>\n
String[] meyveDizisi = meyveler.stream().toArray(String[]::new);<\/code><\/pre>\n
Optional S\u0131n\u0131f\u0131 ve Stream’ler<\/h2>\n
Java 8 ile gelen Optional<\/code> s\u0131n\u0131f\u0131, null<\/code> de\u011ferlerin neden oldu\u011fu NullPointerException<\/code> sorununu \u00e7\u00f6zmek i\u00e7in tasarlanm\u0131\u015ft\u0131r. Bir de\u011ferin var olup olmad\u0131\u011f\u0131n\u0131 temsil eden bir kapsay\u0131c\u0131d\u0131r. Stream API’deki findFirst()<\/code>, findAny()<\/code>, min()<\/code>, max()<\/code>, average()<\/code> gibi baz\u0131 terminal i\u015flemler, bir sonu\u00e7 bulunamayabilece\u011fi durumlarda Optional<\/code> d\u00f6nd\u00fcr\u00fcr.<\/p>\n
List bosListe = new ArrayList<>();\nOptional ilkEleman = bosListe.stream().findFirst(); \/\/ Optional.empty\n\nif (ilkEleman.isPresent()) {\n    System.out.println(ilkEleman.get());\n} else {\n    System.out.println(\"Liste bo\u015f.\"); \/\/ Liste bo\u015f.\n}\n\nString varsayilanDeger = ilkEleman.orElse(\"Varsay\u0131lan\"); \/\/ Varsay\u0131lan\nString hesaplanmisDeger = ilkEleman.orElseGet(() -> \"Hesaplanan\"); \/\/ Hesaplanan\n\ntry {\n    ilkEleman.orElseThrow(() -> new NoSuchElementException(\"Eleman bulunamad\u0131.\"));\n} catch (NoSuchElementException e) {\n    System.out.println(e.getMessage()); \/\/ Eleman bulunamad\u0131.\n}<\/code><\/pre>\n
Optional<\/code> ayr\u0131ca map()<\/code>, flatMap()<\/code>, filter()<\/code> gibi metotlara sahiptir, bu da onu stream benzeri bir \u015fekilde i\u015flemeye olanak tan\u0131r.<\/p>\n
Paralel Stream’ler<\/h2>\n
Stream API’nin en g\u00fc\u00e7l\u00fc \u00f6zelliklerinden biri, stream’leri kolayca paralel hale getirme yetene\u011fidir. Bu, \u00f6zellikle \u00e7ok \u00e7ekirdekli i\u015flemcilerde b\u00fcy\u00fck veri setleri \u00fczerinde performans art\u0131\u015f\u0131 sa\u011flayabilir.<\/p>\n
Paralel Stream Olu\u015fturma<\/h3>\n
Bir koleksiyondan paralel stream olu\u015fturmak i\u00e7in parallelStream()<\/code> metodunu kullanabilirsiniz:<\/p>\n
List sayilar = Arrays.asList(1, 2, 3, 4, 5, 6, 7, 8, 9, 10);\nsayilar.parallelStream().forEach(System.out::println);<\/code><\/pre>\n
Normal bir stream’i paralel stream’e d\u00f6n\u00fc\u015ft\u00fcrmek i\u00e7in parallel()<\/code> metodunu kullanabilirsiniz:<\/p>\n
IntStream.range(1, 1000000).parallel().sum();<\/code><\/pre>\n
Avantajlar\u0131<\/h3>\n
*   Performans Art\u0131\u015f\u0131:<\/strong> \u00d6zellikle CPU yo\u011fun i\u015flemlerde ve b\u00fcy\u00fck veri setlerinde, i\u015f y\u00fck\u00fcn\u00fc birden fazla \u00e7ekirde\u011fe da\u011f\u0131tarak i\u015flem s\u00fcresini \u00f6nemli \u00f6l\u00e7\u00fcde azaltabilir.
\n*   Kolayl\u0131k:<\/strong> Paralel programlama karma\u015f\u0131kl\u0131\u011f\u0131n\u0131 soyutlar; geli\u015ftiricilerin manuel olarak i\u015f par\u00e7ac\u0131\u011f\u0131 y\u00f6netimi yapmas\u0131na gerek kalmaz.<\/p>\n
Dezavantajlar\u0131 ve Dikkat Edilmesi Gerekenler<\/h3>\n
*   Ek Y\u00fck (Overhead):<\/strong> Paralel stream’lerin olu\u015fturulmas\u0131 ve y\u00f6netilmesi bir miktar ek y\u00fck getirir. K\u00fc\u00e7\u00fck veri setleri i\u00e7in bu ek y\u00fck, paralel i\u015flemenin faydalar\u0131n\u0131 g\u00f6lgede b\u0131rakabilir.
\n*   Durum Bilgisi Olan (Stateful) \u0130\u015flemler:<\/strong> distinct()<\/code>, sorted()<\/code>, limit()<\/code> gibi durum bilgisi olan ara i\u015flemler, paralel stream’lerde ek maliyetlere neden olabilir veya beklenen sonu\u00e7lar\u0131 vermeyebilir. Payla\u015f\u0131lan mutable durumdan (shared mutable state) ka\u00e7\u0131n\u0131lmal\u0131d\u0131r.
\n*   S\u0131ra Garantisi:<\/strong> forEach()<\/code> gibi i\u015flemler paralel stream’lerde elemanlar\u0131n i\u015flenme s\u0131ras\u0131n\u0131 garanti etmez. E\u011fer s\u0131ra \u00f6nemliyse forEachOrdered()<\/code> kullan\u0131lmal\u0131d\u0131r.
\n*   Fork\/Join Framework:<\/strong> Paralel stream’ler, dahili olarak Java’n\u0131n Fork\/Join Framework’\u00fcn\u00fc kullan\u0131r. Bu, varsay\u0131lan olarak ortak bir ForkJoinPool<\/code> kullan\u0131r. Bu havuz, uygulaman\u0131zdaki di\u011fer paralel g\u00f6revlerle \u00e7ak\u0131\u015fabilir.
\n*   Veri Yap\u0131s\u0131n\u0131n \u00d6zellikleri:<\/strong> ArrayList<\/code> ve diziler gibi rastgele eri\u015fime sahip veri yap\u0131lar\u0131, paralel stream’ler i\u00e7in daha uygunken, LinkedList<\/code> gibi ard\u0131\u015f\u0131k eri\u015fim gerektiren yap\u0131lar daha az performansl\u0131 olabilir.<\/p>\n
Ne Zaman Kullan\u0131lmal\u0131?<\/strong>
\n*   B\u00fcy\u00fck veri setleri \u00fczerinde CPU yo\u011fun i\u015flemler yap\u0131l\u0131yorsa.
\n*   \u0130\u015flemler ba\u011f\u0131ms\u0131z ve yan etkisiz (side-effect-free) ise.
\n*   S\u0131ra \u00f6nemli de\u011filse veya forEachOrdered()<\/code> gibi metotlarla y\u00f6netilebiliyorsa.<\/p>\n
Ne Zaman Ka\u00e7\u0131n\u0131lmal\u0131?<\/strong>
\n*   K\u00fc\u00e7\u00fck veri setleri \u00fczerinde \u00e7al\u0131\u015f\u0131l\u0131yorsa.
\n*   I\/O yo\u011fun i\u015flemler yap\u0131l\u0131yorsa (genellikle CPU de\u011fil, I\/O beklemesi olur).
\n*   Durum bilgisi olan (stateful) lambda ifadeleri kullan\u0131l\u0131yorsa.
\n*   Performans testleri paralel stream’in fayda sa\u011flamad\u0131\u011f\u0131n\u0131 g\u00f6steriyorsa.<\/p>\n
Yayg\u0131n Kullan\u0131m Senaryolar\u0131 ve \u00d6rnekler<\/h2>\n
Stream API, bir\u00e7ok yayg\u0131n programlama g\u00f6revini basitle\u015ftirir.<\/p>\n
*   Veri Filtreleme ve D\u00f6n\u00fc\u015ft\u00fcrme:<\/strong> Bir listeden belirli ko\u015fullar\u0131 sa\u011flayan elemanlar\u0131 se\u00e7ip, bu elemanlar\u0131 farkl\u0131 bir formata d\u00f6n\u00fc\u015ft\u00fcrmek.<\/p>\n
List urunler = Arrays.asList(\"Laptop\", \"Klavye\", \"Mouse\", \"Monit\u00f6r\", \"Kamera\");\n    List uzunUrunler = urunler.stream()\n                                      .filter(u -> u.length() > 5)\n                                      .map(String::toUpperCase)\n                                      .collect(Collectors.toList()); \/\/ [LAPTOP, KLAVYE, MON\u0130T\u00d6R, KAMERA]<\/code><\/pre>\n
*   Toplu Veri \u0130\u015fleme (Aggregation):<\/strong> Say\u0131sal verilerin toplam\u0131n\u0131, ortalamas\u0131n\u0131, minimum veya maksimum de\u011ferini bulmak.<\/p>\n
List fiyatlar = Arrays.asList(1200.50, 450.00, 75.25, 2300.75);\n    double ortalamaFiyat = fiyatlar.stream()\n                                    .mapToDouble(Double::doubleValue)\n                                    .average()\n                                    .orElse(0.0); \/\/ 1006.625<\/code><\/pre>\n
*   Raporlama (Gruplama, \u00d6zetleme):<\/strong> Verileri belirli kriterlere g\u00f6re gruplamak ve her grup i\u00e7in \u00f6zet bilgiler \u00e7\u0131karmak.<\/p>\n
class Calisan {\n        String ad;\n        String departman;\n        double maas;\n        \/\/ constructor, getters\n    }\n    List calisanlar = Arrays.asList(new Calisan(\"Ay\u015fe\", \"IT\", 6000), new Calisan(\"Can\", \"HR\", 5000), new Calisan(\"Fatma\", \"IT\", 7000));\n    Map departmanMaasOrtalamalari = calisanlar.stream()\n                                                              .collect(Collectors.groupingBy(\n                                                                  c -> c.departman,\n                                                                  Collectors.averagingDouble(c -> c.maas)\n                                                              )); \/\/ {IT=6500.0, HR=5000.0}<\/code><\/pre>\n
*   Dosya \u0130\u015fleme:<\/strong> Bir dosyan\u0131n her sat\u0131r\u0131n\u0131 okuyup i\u015flemek.<\/p>\n
\/\/ Yukar\u0131daki Files.lines \u00f6rne\u011fine bak\u0131n\u0131z.<\/code><\/pre>\n
En \u0130yi Uygulamalar ve Performans \u0130pu\u00e7lar\u0131<\/h2>\n
Stream API’yi etkin bir \u015fekilde kullanmak i\u00e7in baz\u0131 en iyi uygulamalar\u0131 ve performans ipu\u00e7lar\u0131n\u0131 g\u00f6z \u00f6n\u00fcnde bulundurmak \u00f6nemlidir.<\/p>\n
*   Tembel De\u011ferlendirmeyi Anlay\u0131n:<\/strong> Stream’ler, bir terminal i\u015flem \u00e7a\u011fr\u0131lana kadar \u00e7al\u0131\u015fmaz. Bu, i\u015flem hatt\u0131n\u0131 olu\u015ftururken gereksiz ara i\u015flemlerden ka\u00e7\u0131nman\u0131za yard\u0131mc\u0131 olur.
\n*   Stream’leri Tekrar Kullanmay\u0131n:<\/strong> Bir stream, terminal i\u015flemden sonra t\u00fcketilir ve tekrar kullan\u0131lamaz. Yeniden i\u015flem yapmak i\u00e7in yeni bir stream olu\u015fturulmal\u0131d\u0131r.
\n*   K\u0131sa Devre (Short-Circuiting) \u0130\u015flemlerini Kullan\u0131n:<\/strong> limit()<\/code>, findFirst()<\/code>, anyMatch()<\/code>, allMatch()<\/code>, noneMatch()<\/code> gibi i\u015flemler, t\u00fcm stream’i i\u015flemek zorunda kalmadan bir sonu\u00e7 d\u00f6nd\u00fcrebilir. Bu, performans\u0131 \u00f6nemli \u00f6l\u00e7\u00fcde art\u0131rabilir. \u00d6rne\u011fin, bir listede belirli bir eleman\u0131n olup olmad\u0131\u011f\u0131n\u0131 kontrol etmek i\u00e7in anyMatch()<\/code> kullanmak, t\u00fcm listeyi dola\u015fan bir filter().count() > 0<\/code> kombinasyonundan daha verimli olacakt\u0131r.
\n*   Mutable State’ten Ka\u00e7\u0131n\u0131n:<\/strong> Stream i\u015flemleri genellikle durum bilgisiz (stateless) olmal\u0131d\u0131r. Lambda ifadeleriniz i\u00e7inde d\u0131\u015far\u0131daki de\u011fi\u015fkenleri de\u011fi\u015ftirmek (side-effects) hatalara ve \u00f6ng\u00f6r\u00fclemeyen davran\u0131\u015flara yol a\u00e7abilir, \u00f6zellikle paralel stream’lerde. forEach()<\/code> veya peek()<\/code> gibi istisnalar d\u0131\u015f\u0131nda, yan etkilerden ka\u00e7\u0131n\u0131n.
\n*   Primitive Stream’leri Kullan\u0131n:<\/strong> IntStream<\/code>, LongStream<\/code>, DoubleStream<\/code> gibi ilkel stream’ler, Stream<\/code> gibi kutulanm\u0131\u015f (boxed) stream’lere g\u00f6re daha performansl\u0131d\u0131r, \u00e7\u00fcnk\u00fc otomatik kutulama\/kutudan \u00e7\u0131karma maliyetini ortadan kald\u0131r\u0131rlar.
\n*   Paralel Stream’leri Dikkatli Kullan\u0131n:<\/strong> Paralel stream’ler performans art\u0131\u015f\u0131 sa\u011flayabilir, ancak her zaman en iyi \u00e7\u00f6z\u00fcm de\u011fildir. K\u00fc\u00e7\u00fck veri setleri, I\/O yo\u011fun i\u015flemler veya durum bilgisi olan i\u015flemler i\u00e7in paralel stream’ler ek y\u00fck getirebilir veya sorunlara yol a\u00e7abilir. Performans\u0131 test edin ve yaln\u0131zca fayda sa\u011flad\u0131\u011f\u0131nda kullan\u0131n.
\n*   Optional<\/code>‘\u0131 Do\u011fru Kullan\u0131n:<\/strong> null<\/code> kontrollerinden ka\u00e7\u0131nmak i\u00e7in Optional<\/code>‘\u0131n metotlar\u0131n\u0131 (\u00f6rne\u011fin orElse()<\/code>, orElseGet()<\/code>, ifPresent()<\/code>) kullan\u0131n. get()<\/code> metodunu yaln\u0131zca isPresent()<\/code> ile kontrol ettikten sonra veya de\u011ferin kesinlikle var oldu\u011fundan eminseniz kullan\u0131n.
\n*   Collectors<\/code> S\u0131n\u0131f\u0131n\u0131 Ke\u015ffedin:<\/strong> Collectors<\/code> s\u0131n\u0131f\u0131, stream elemanlar\u0131n\u0131 toplamak i\u00e7in geni\u015f bir yelpazede g\u00fc\u00e7l\u00fc ve optimize edilmi\u015f metotlar sunar. Kendi \u00f6zel Collector<\/code>‘\u0131n\u0131z\u0131 yazmadan \u00f6nce mevcut metotlara g\u00f6z at\u0131n.<\/p>\n
Sonu\u00e7<\/h2>\n
Java 8 Stream API, modern Java geli\u015ftirmesinde veri i\u015fleme \u015feklini d\u00f6n\u00fc\u015ft\u00fcren devrim niteli\u011finde bir \u00f6zelliktir. Daha k\u0131sa, daha okunabilir, daha deklaratif ve daha az hata e\u011filimli kod yazmam\u0131z\u0131 sa\u011flayarak, geli\u015ftiricilerin koleksiyonlar \u00fczerindeki karma\u015f\u0131k i\u015flemleri daha kolay ifade etmelerine olanak tan\u0131r. Fonksiyonel programlama paradigmas\u0131n\u0131 Java’ya entegre etmesiyle, kod kalitesini art\u0131r\u0131r ve \u00f6zellikle paralel i\u015flemlerle b\u00fcy\u00fck veri setlerinin i\u015flenmesinde \u00f6nemli performans avantajlar\u0131 sunar.<\/p>\n
Stream API’nin temel kavramlar\u0131n\u0131 (kaynak, ara i\u015flemler, terminal i\u015flemler, tembel de\u011ferlendirme, de\u011fi\u015fmezlik) anlamak, bu g\u00fcc\u00fc tam olarak kullanman\u0131n anahtar\u0131d\u0131r. Do\u011fru kullan\u0131m senaryolar\u0131nda paralel stream’lerden yararlanmak ve Optional<\/code> s\u0131n\u0131f\u0131 ile null<\/code> sorunlar\u0131n\u0131 y\u00f6netmek, daha sa\u011flam ve verimli uygulamalar geli\u015ftirmeye yard\u0131mc\u0131 olacakt\u0131r. Java ekosistemi geli\u015ftik\u00e7e, Stream API’nin \u00f6nemi artmaya devam edecek ve Java geli\u015ftiricilerinin ara\u00e7 kutusunun vazge\u00e7ilmez bir par\u00e7as\u0131 olarak kalacakt\u0131r.<\/body><\/p>\n","protected":false},"excerpt":{"rendered":"Java 8 Stream API: Modern Veri \u0130\u015flemenin G\u00fcc\u00fc\nJava 8 ile birlikte tan\u0131t\u0131lan Stream API, koleksiyonlar \u00fczerinde fonksiyonel stil operasyonlar g","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"csco_page_header_type":"","csco_page_load_nextpost":"","csco_page_subscribe_form":"","csco_page_contact_form":"","footnotes":""},"categories":[1408],"tags":[],"class_list":{"0":"post-35400","1":"post","2":"type-post","3":"status-publish","4":"format-standard","6":"category-java","7":"cs-entry","8":"cs-video-wrap"},"yoast_head":"\nJava 8 Stream API: Modern Veri \u0130\u015flemenin G\u00fcc\u00fc - Kodlar\u0131n Gizemli D\u00fcnyas\u0131<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/fatihsoysal.com\/blog\/java-8-stream-api-modern-veri-islemenin-gucu\/\" \/>\n<meta property=\"og:locale\" content=\"tr_TR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Java 8 Stream API: Modern Veri \u0130\u015flemenin G\u00fcc\u00fc\" \/>\n<meta property=\"og:description\" content=\"Java 8 Stream API: Modern Veri \u0130\u015flemenin G\u00fcc\u00fc Java 8 ile birlikte tan\u0131t\u0131lan Stream API, koleksiyonlar \u00fczerinde fonksiyonel stil operasyonlar g\" \/>\n<meta property=\"og:url\" content=\"https:\/\/fatihsoysal.com\/blog\/java-8-stream-api-modern-veri-islemenin-gucu\/\" \/>\n<meta property=\"og:site_name\" content=\"Kodlar\u0131n Gizemli D\u00fcnyas\u0131\" \/>\n<meta property=\"article:published_time\" content=\"2025-11-29T04:40:47+00:00\" \/>\n<meta name=\"author\" content=\"Fatih Soysal\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:label1\" content=\"Yazan:\" \/>\n\t<meta name=\"twitter:data1\" content=\"Fatih Soysal\" \/>\n\t<meta name=\"twitter:label2\" content=\"Tahmini okuma s\u00fcresi\" \/>\n\t<meta name=\"twitter:data2\" content=\"17 dakika\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/java-8-stream-api-modern-veri-islemenin-gucu\/#article\",\"isPartOf\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/java-8-stream-api-modern-veri-islemenin-gucu\/\"},\"author\":{\"name\":\"Fatih Soysal\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\"},\"headline\":\"Java 8 Stream API: Modern Veri \u0130\u015flemenin G\u00fcc\u00fc\",\"datePublished\":\"2025-11-29T04:40:47+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/java-8-stream-api-modern-veri-islemenin-gucu\/\"},\"wordCount\":2531,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#\/schema\/person\/002a254750921dcfd568a99e48240dd1\"},\"articleSection\":[\"Java\"],\"inLanguage\":\"tr\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\/\/fatihsoysal.com\/blog\/java-8-stream-api-modern-veri-islemenin-gucu\/#respond\"]}],\"copyrightYear\":\"2025\",\"copyrightHolder\":{\"@id\":\"https:\/\/fatihsoysal.com\/blog\/#organization\"}},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/fatihsoysal.com\/blog\/java-8-stream-api-modern-veri-islemenin-gucu\/\",\"url\":\"https:\/\/fatihsoysal.com\/blog\/java-8-stream-api-modern-veri-islemenin-gucu\/\",\"name\":\"Java 8 Stream API: Modern Veri \u0130\u015flemenin G\u00fcc\u00fc - 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