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Introduction and HDInsight best practices
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- 2. • The mosttrusted and compliant platform Azure HDInsight A secure and managed Apache Hadoop and Spark platform for building data lakes in the Cloud @ashishth
- 3. hot path cold path Serving-layer datasources consumers Governance HDFS Compliant Storage (Azure Data Lake Store Gen 2) Meta data Management Security / Access Control Ingest real-time data with Kafka Real Time NOSQL Store (HBase) ETL (Apache Spark/Hive/Pig) Ingest batch data AdHoc Query in DataLake Serving Layer Apache Spark/Hive LLAP/ Presto Store real-time data for long term analysis Orchestration Corporate Data Devices & Sensors Advanced Analytics & Data Science Machine Learning R, Python, APIs Analytics Data Exploration Corporate Reporting Self-Service BI Streaming/Real- Time/ Application Stream Processing (Storm/Apache Spark) @ashishth
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- 5. HDInsight Cluster Gateways Head Node1 Head Node 2 Worker Node Worker Node Worker Node Worker Node Zookeeper1 Zookeeper1 Zookeeper1 Hive Metastore YARN Internal: https://cluster-int.azurehdinsight.net/APIs External: https://cluster.azurehdinsight.net/APIs @ashishth
- 6. VS and VSCODE IntelliJ EclipseZeppelin Jupyter R Studio @ashishth
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- 9. Data Qty NetworkBandwidth 45 Mbps (T3) 100 Mbps 1 Gbps 1 TB 2 days 1 day 2 hours 10 TB 22 days 10 days 1 day 35 TB 76 days 34 days 3 days 80 TB 173 days 78 days 8 days 100 TB 216 days 97 days 10 days 200 TB 1 year 194 days 19 days 500 TB 3 years 1 year 49 days 1 PB 6 years 3 years 97 days 2 PB 12 years 5 years 194 days @ashishth
- 10. Network Transfer withTLS • Over Internet • Express Route • Data Box online Transfer Shipping data offline • Data Box offline data transfer @ashishth
- 11. USB 3.1 SSDdisks Order up to 5 in each pack Ruggedized, self-contained appliances 100 TB 8 TB, up to 40 TB 1 PB @ashishth Use Azure Data Box to migrate data from an on-premises HDFS store to Azure Storage
- 12. Type Latency (Consistency of latency) Workloads Bandwidth Key Benefits ADLS Gen 2 Hierarchical 10-50ms (Medium) HDInsight 3.6 & 4.0 Unconstrained Atomic Rename, File Folder level ACL’s Standard BLOB Object Store 10-50ms (Medium) HDInsight 3.6 & 4.0 Unconstrained Mature Premium BLOB Object Store ~5ms (High) HBase in Preview Unconstrained Fast Premium Managed Disks Hierarchical ~5ms (High) Kafka, HBase in preview Based on disk Consistent latency ADLS Gen 1 Hierarchical 10-100ms (Low) HDInsight 3.6( No HBase) High Atomic Rename, File Folder level ACL’s @ashishth
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- 15. RegionServer Storage Client -Put -Update -Get -Delete Log Flusher Remote store writepath challenges with Write Ahead Log Insert Update Get Delete Sync Operation • Inconsistent Latencies • High latencies @ashishth
- 16. RegionServer Premium Managed Disk(s) Client -Put -Update -Get -Delete Log Flusher Insert Update GetDelete Sync Operation Introducing Premium Managed disk for WAL • Consistent Latencies • Low latencies • Data Durability @ashishth
- 17. RegionServer Client -Put -Delete -Get Region Region Region Log Flusher Memstore HFile Memstore HFile Memstore HFile Low latency workloadHBase/ Small write @ashishth Storage Premium Managed Disk(s)
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- 22. Workload Caching OptionsKey benefits Spark Spark IO Cache Up to ~8 to 10x perf improvements HBase & Phoenix Bucket cache Up 5-10x perf gains on recently read or written data Hive + LLAP LLAP Intelligent cache/Result Cache Up to ~4-100X gain on cached data @ashishth
- 23. Azure Data LakeStorage INSTANCE CORE RAM TEMP SSD D1 v2 1 3.50 GiB 50 GiB D2 v2 2 7.00 GiB 100 GiB D3 v2 4 14.00 GiB 200 GiB D4 v2 8 28.00 GiB 400 GiB D5 v2 16 56.00 GiB 800 GiB • Significant Spark performance speed up with IO cache (up to 9X perf gains) • Automatic cache resource management • DRAM + Temp SSD makes large cache pool @ashishth@ashishth
- 24. PERIMETER Isolate clusters withinVNETs Service Endpoint support for WASB, Azure DB, Cosmos DB Restrict outbound traffic using NVAs* AUTHENTICATION Azure Active Directory Kerberos with Active Directory AUTHORIZATION Role-Based Access Control Apache Ranger based Access Control DATA PROTECTION Encryption on-the-wire with HTTPS enforced Encryption at Rest using Azure Key Vault Auditing of all data operations and configuration changes @ashishth
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- 29. • hdfs dfsadmin-D 'fs.default.name=hdfs://mycluster/' -safemode get # A report that shows the • details of HDFS state: hdfs dfsadmin -D 'fs.default.name=hdfs://mycluster/' -report # Get HDFS • out of safe mode hdfs dfsadmin -D 'fs.default.name=hdfs://mycluster/' -safemode leave # Get • HDFS into safe mode hdfs dfsadmin -D 'fs.default.name=hdfs://mycluster/' -safemode enter @ashishth
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- 31. Apache Ambari AzureLog Analytics IntegrationHDInsight Cluster Metrics @ashishth
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Editor's Notes
- #3 Azure HDInsight is a secure and managed platform for building data lakes on Azure based on the Apache Hadoop and Spark frameworks. So, what all does HDInsight have to offer? Reliable Open Source analytics with an Industry leading SLA HDInsight allows you to easily spin up open source cluster types guaranteed with the industry’s best 99.9% SLA and 24/7 support. We guarantee this SLA for the entire big data solution, not just the VM instances. HDInsight is architected for full redundancy and high availability including head node replication, data geo-replication, and built-in standby NameNode making HDInsight resilient to critical failures not addressed in standard Hadoop implementations. Azure also offers cluster monitoring and 24x7 enterprise support backed by Microsoft and Hortonworks with 37 combined committers for Hadoop core, more than all other managed cloud providers combined to support your deployment and the ability to fix and commit code back to Hadoop. Enterprise Grade Security & Monitoring HDInsight protects your data assets and easily extends your on-premise security and governance controls to the cloud. We feature single sign-on (SSO), multi-factor authentication and seamless management of millions of identities through Azure Active Directory. You can authorize users and groups with fine-grained access control policies over all your enterprise data with Apache Ranger. HDInsight meets HIPAA, PCI, SOC compliance, ensuring your enterprise data assets are always protected with the highest security and regulatory compliance. To ensure the highest level of business continuity, HDInsight extends capabilities for alerting, monitoring, defining pre-emptive actions, and enhanced workload protection through native integration with Azure Operations Management Suite (OMS). Most Productive platform for developers and scientists HDInsight offers developers tailored experiences through rich productivity suites for Hadoop & Spark with integrated development environments using Visual Studio, Eclipse, and IntelliJ supporting Scala, Python, R, Java, and .Net. HDInsight gives data scientists the ability to create narratives that combine code, statistical equations, and visualizations that tell a story about the data through integration to the two most popular notebooks: Jupyter and Zeppelin. HDInsight is also the only managed cloud Hadoop solution with integration to Microsoft R Server. Multi-threaded math libraries and transparent parallelization in R Server means handling up to 1000x more data and up to 50x faster speeds than open source R—helping you train more accurate models for better predictions than previously possible. Cost effective cloud scale HDInsight has decoupled compute and storage, enabling you to cost-effectively scale workloads up or down, independent of storage. Local storage can still be used for caching and fast I/O. Spark and interactive Hive users can choose SSD memory for interactive performance; while Kafka users can retain all streaming data in premium managed disks. You only pay for the compute and storage you use and are given the ability to choose any Azure VM types that enables the best utilization of resources. A recent study showed HDInsight delivering 63% lower TCO than deploying Hadoop on premises over 5 years.* Integration with leading Productivity Applications In the broader ecosystem for Hadoop, there is a thriving market of independent software vendors (ISVs) who provide value added solutions. Through a unique design where every cluster is extended with edge nodes and script action, HDInsight lets customers spin up Hadoop and Spark clusters pre-integrated and pre-tuned with any ISV application out-of-the-box. Datameer, Cask, AtScale, StreamSets are few such applications, which are very popular on the HDInsight platform today. Easy for administrators to manage With HDInsight, administrators can deploy Hadoop in the cloud without buying new hardware or incurring other up-front costs. There’s also no time-consuming installation or set up. There is also no need to patch the operating system or upgrade the Hadoop versions. Azure does it for you. Launch your first cluster in minutes.
- #6 Before I describe specific capabilities and value propositions of HDInsight, let us take a quick look at the architecture of a HDInsight cluster. We will build upon this when we talk about security later on in the presentation. First off, a key difference between an on-premise Hadoop cluster and a HDInsight cluster is that with HDInsight, the storage and compute layers are separated. This allows for storage and compute to be scaled independently of each other. We have seen in numerous customer cases, that trying to combine storage and compute on to a single cluster often leads to underutilization of one or the other or both. With HDInsight, you can keep loading data in to Azure Storage Gen1 or Gen2 or in WASB. And you can create small or large clusters as and when needed. Each HDInsight cluster comes with 2 gateway nodes, 2 head nodes and 3 ZooKeeper nodes. In most cases, these are free of charge. As we will discuss later, we provision multiple of these nodes to ensure high availability. Each HDInsight cluster lives within a VNET. The gateway nodes are the ONLY public endpoints accessible from outside the VNET. As we will see later, this architecture allows you to securely lock down your HDInsight cluster.
- #9 Build 2015
- #11 Transfer data over network with TLS Over internet - You can transfer data to Azure storage over a regular internet connection using any one of several tools such as: Azure Storage Explorer, AzCopy, Azure Powershell, and Azure CLI. See Moving data to and from Azure Storage for more information. Express Route - ExpressRoute is an Azure service that lets you create private connections between Microsoft datacenters and infrastructure that’s on your premises or in a colocation facility. ExpressRoute connections do not go over the public Internet, and offer higher security, reliability, and speeds with lower latencies than typical connections over the Internet. For more information, see Create and modify an ExpressRoute circuit. Data Box online data transfer - Data Box Edge and Data Box Gateway are online data transfer products that act as network storage gateways to manage data between your site and Azure. Data Box Edge, an on-premises network device, transfers data to and from Azure and uses artificial intelligence (AI)-enabled edge compute to process data. Data Box Gateway is a virtual appliance with storage gateway capabilities. For more information, see Azure Data Box Documentation - Online Transfer. Shipping data Offline Import / Export service - you can send physical disks to Azure and they will be uploaded for you. For more information, see What is Azure Import/Export service?. Data Box offline data transfer - Data Box, Data Box Disk, and Data Box Heavy devices help you transfer large amounts of data to Azure when the network isn’t an option. These offline data transfer devices are shipped between your organization and the Azure datacenter. They use AES encryption to help protect your data in transit, and they undergo a thorough post-upload sanitization process to delete your data from the device. For more information, see Azure Data Box Documentation - Offline Transfer.