October 2024
Intermediate to advanced
636 pages
20h 29m
German
Content preview from Architektur von modernen Datenplattformen
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Teil III. Hadoop in die Cloud bringen
In den vorangegangenen Kapiteln haben wir uns mit dem Aufbau von Hadoop-Clustern beschäftigt, die den Anforderungen von Unternehmen entsprechen. Die Cloud-Technologie ermöglicht es, die gesamte Informationstechnologie als vollständig programmierbare und automatisierte Dienste zu nutzen. So werden zum Beispiel Speicherung, Netzwerke und Server zu Infrastructure as a Service (IaaS) und Software auf Plattformebene, wie z. B. Datenbankimplementierungen oder Zugriffsverwaltungssoftware, zu Platform as a Service (PaaS). Der hohe Grad an Programmierbarkeit und Automatisierung ermöglicht es dem Kunden, jede Ebene - von IaaS bis PaaS - fast vollständig selbst zu steuern und anzupassen.
Bevor Public Cloud Computing in großem Maßstab Teil des IT-Mainstreams wurde, galt Virtualisierung für Hadoop meist als Anti-Muster. Das lag zum großen Teil an der verteilten Natur von Hadoop und der Tatsache, dass es für einen effizienten Betrieb auf lokale Festplatten auf jedem Server angewiesen ist. Der Betrieb von Hadoop in der Cloud läuft daher oft auf eine Frage hinaus: Kann ich alle meine Daten in der Cloud speichern und effizient verarbeiten? Die Antwort lautet ja.
Öffentliche Cloud-Provider arbeiten in einer solchen Größenordnung (oft als Hyperscale bezeichnet), dass Hadoop-Umgebungen und ihr hoher Bedarf an E/A-Durchsatz zu vernünftigen Preisen untergebracht werden können. Inzwischen haben auch die Hadoop-Vertreiber auf die große Chance von Hadoop in der Cloud ...
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