{
  "core": {
    "name": "APEXCORE",
    "url": "https://issues.apache.org/jira/",
    "jiras": [
      {
        "expand": "operations,editmeta,changelog,transitions,renderedFields",
        "id": "12919332",
        "self": "https://issues.apache.org/jira/rest/api/2/issue/12919332",
        "key": "APEXCORE-163",
        "fields": {
          "summary": "Dynamic application property changes",
          "description": "Apex support modification of operator properties at runtime but the current implemenations has the following shortcomings.\r\n\r\n1. Property is not set across all partitions on the same window as individual partitions can be on different windows when property change is initiated from client resulting in inconsistency of data for those windows. I am being generous using the word inconsistent.\r\n2. Sometimes properties need to be set on more than one logical operators at the same time to achieve the change the user is seeking. Today they will be two separate changes happening on two different windows again resulting in inconsistent data for some windows. These would need to happen as a single transaction.\r\n3. If there is an operator failure before a committed checkpoint after an operator property is dynamically changed the operator will restart with the old property and the change will not be re-applied.\r\n\r\nTim and myself did some brainstorming and we have a proposal to overcome these shortcomings. The main problem in all the above cases is that the property changes are happening out-of-band of data flow and hence independent of windowing. The proposal is to bring the property change request into the in-band dataflow so that they are handled consistently with windowing and handled distributively.\r\n\r\nThe idea is to inject a special property change tuple containing the property changes and the identification information of the operator's they affect into the dataflow at the input operator. The tuple will be injected at window boundary after end window and before begin window and as this tuple flows through the DAG the intended operators properties will be modifed. They will all be modified consistently at the same window. The tuple can contain more than one property changes for more than one logical operators and the change will be applied consistently to the different logical operators at the same window. In case of failure the replay of tuples will ensure that the property change gets reapplied at the correct window.",
          "fixVersions": [],
          "priority": {
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        "expand": "operations,editmeta,changelog,transitions,renderedFields",
        "id": "12919400",
        "self": "https://issues.apache.org/jira/rest/api/2/issue/12919400",
        "key": "APEXCORE-231",
        "fields": {
          "summary": "Ability to change attributes at runtime",
          "description": "The Apex engine supports many platform level attributes like operator memory, application window count, container jvm options etc. Today these can only be set at application launch time and cannot be changed once the application is running.\r\n\r\nThis issue is to add the ability to change the attributes dynamically even as the application is running. The mechanics of an user requesting the attribute change can be similar to how a user requests property change via the command line client.\r\n\r\nSince each attribute is different the actual backend implementation to affect the changes will most likely be custom handling for different attributes but during the implementation process  hopefully some common themes emerge and some amount of reuse possible.",
          "fixVersions": [],
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      },
      {
        "expand": "operations,editmeta,changelog,transitions,renderedFields",
        "id": "12919401",
        "self": "https://issues.apache.org/jira/rest/api/2/issue/12919401",
        "key": "APEXCORE-232",
        "fields": {
          "summary": "Ability to add new processing code to the DAG",
          "description": "There are scenarios when new processing code needs to be added to an already running application. There are two scenarios.\r\n\r\na. A bug is discovered in an operator and an existing operator in the running DAG needs to be replaced. The platform supports shutting down and resuming an application which could be use as a first cut way to do this but there are a couple of drawbacks.\r\n       i. This only works when the input source has memory, if it doesn't the messages received during the time the application is down are lost.\r\n      ii. Depending on the complexity and state of the application it may take some time for this entire process and the application to get back to running state and this delay may not be acceptable for the downstream components that depend on the output of this application.\r\n\r\nb. A new operator needs to be added to the DAG to take data from an existing operator and do some additional processing. Today this is supported as long as the code for the operator is already in the application libraries. Often this will not be the case as users will not know what the operator will be beforehand when the application is originally launched.",
          "fixVersions": [],
          "priority": {
            "self": "https://issues.apache.org/jira/rest/api/2/priority/3",
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            "id": "3"
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      },
      {
        "expand": "operations,editmeta,changelog,transitions,renderedFields",
        "id": "12919402",
        "self": "https://issues.apache.org/jira/rest/api/2/issue/12919402",
        "key": "APEXCORE-233",
        "fields": {
          "summary": "Ability to specify single instance objects in configuration",
          "description": "There are scenarios where the same object instance needs to be specified for two attributes. Example is partitioner and stats listener, for partitioners that need to affect partitoning based on operator stats the same instance needs to be both. This is not possible to specify using a property file today as it will create two separate instances and can only be done in Java code today. The issue is to request adding this feature.",
          "fixVersions": [],
          "priority": {
            "self": "https://issues.apache.org/jira/rest/api/2/priority/3",
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        }
      },
      {
        "expand": "operations,editmeta,changelog,transitions,renderedFields",
        "id": "12919403",
        "self": "https://issues.apache.org/jira/rest/api/2/issue/12919403",
        "key": "APEXCORE-234",
        "fields": {
          "summary": "Investigate other ways to specify properties in property files",
          "description": "The current property file specification follows the hadoop configuration file format and this has led to some drawbacks. \r\n    a. The names for the properties and attributes are verbose in the configuration file. \r\n    b. When there are nested properties in operators the syntax deviates from the bean specification because it introduces some specific keywords in the specification like .prop and ,attr.\r\n\r\nThere will already be some changes afoot based on the following\r\n   a. When adding ability to specify single instance attributes (https://malhar.atlassian.net/browse/APEXCORE-233) implementing it in the current syntax may not be possible or lead to very unwieldy syntax.\r\n   b. There are also other ideas such as one from David to have the ability to specify global application level attributes which possible require rethinking the current syntax.\r\n\r\nUsers have also asked for an easier and more consistent way to specify these properties.  This issue is to track the ideas and progress of these changes.",
          "fixVersions": [],
          "priority": {
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            "id": "3"
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        }
      },
      {
        "expand": "operations,editmeta,changelog,transitions,renderedFields",
        "id": "12919404",
        "self": "https://issues.apache.org/jira/rest/api/2/issue/12919404",
        "key": "APEXCORE-235",
        "fields": {
          "summary": "Improve support for batch processing",
          "description": "Apex can be used for real-time and batch processing as it stands, but there are some aspects of batch processing that can be better supported through explicit constructs. This ticket can serve as umbrella for various features.",
          "fixVersions": [],
          "priority": {
            "self": "https://issues.apache.org/jira/rest/api/2/priority/3",
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            "id": "3"
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            }
          }
        }
      },
      {
        "expand": "operations,editmeta,changelog,transitions,renderedFields",
        "id": "12922256",
        "self": "https://issues.apache.org/jira/rest/api/2/issue/12922256",
        "key": "APEXCORE-289",
        "fields": {
          "summary": "Encrypted Streams in Apex DAG",
          "description": "We should support encrypted streams in a DAG for Apex.\r\nBasically there will be 2 ways user can configure the streams for encryption:\r\n1) App wide attributes- Using which all the stream in the DAG will have encrypted channel.\r\n2) Stream based attribute - Using this user can set a certain stream to flow over encrypted channel.\r\n\r\nEncrypted for the streams should done at Network/Buffer Server levels.",
          "fixVersions": [],
          "priority": {
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            "id": "3"
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          }
        }
      },
      {
        "expand": "operations,editmeta,changelog,transitions,renderedFields",
        "id": "12955475",
        "self": "https://issues.apache.org/jira/rest/api/2/issue/12955475",
        "key": "APEXCORE-418",
        "fields": {
          "summary": "Support for Mesos",
          "description": "Today Apex has two modes of execution: Embedded mode (everything running in a single JVM) and YARN. There has been a few questions around native support for Mesos. A cursory look suggests that Mesos support can be added by reimplementing the YARN specific portions in the master (AppMasterService, ContainerLauncher) and limited changes to the streaming container driver.\r\n\r\nMesos has a different model of resource allocation: The master offers resources to the framework while in YARN resources are requested. Apex master needs to implement the \"framework scheduler\" that is responsible to accept the resources and control the tasks.\r\n\r\nhttp://mesos.apache.org/documentation/latest/app-framework-development-guide/\r\n\r\nTasks are launched through executors, command line and docker executors are provided.  \r\n\r\nApex also requires support to deploy the dependencies to the nodes on which the streaming containers are launched. YARN supports that through resource localization. Mesos supports this through the fetcher, which can copy the resources to the slave node.\r\n\r\nhttp://mesos.apache.org/documentation/latest/fetcher/\r\n",
          "fixVersions": [],
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            "id": "3"
          },
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        }
      },
      {
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        "id": "12992322",
        "self": "https://issues.apache.org/jira/rest/api/2/issue/12992322",
        "key": "APEXCORE-498",
        "fields": {
          "summary": "Named Checkpoints - Checkpoint the DAG with a name/tag and start the app from that point",
          "description": "Named Checkpoints \r\n\r\n1. Ability to tag/name the checkpoints\r\n2. On demand - checkpoint the DAG\r\n3. Start the app from the named checkpoints\r\n\r\nAll checkpoints that happened before the committed window is deleted but the named checkpoints won't be deleted.",
          "fixVersions": [],
          "priority": {
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              "id": 2,
              "key": "new",
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      }
    ],
    "versions": [
      {
        "self": "https://issues.apache.org/jira/rest/api/2/version/12333945",
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        "name": "3.0.1",
        "archived": true,
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        "projectId": 12318823
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      {
        "self": "https://issues.apache.org/jira/rest/api/2/version/12335594",
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      {
        "self": "https://issues.apache.org/jira/rest/api/2/version/12334814",
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        "name": "3.3.1",
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        "projectId": 12318823
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        "self": "https://issues.apache.org/jira/rest/api/2/version/12335725",
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  },
  "malhar": {
    "name": "APEXMALHAR",
    "url": "https://issues.apache.org/jira/",
    "jiras": [
      {
        "expand": "operations,editmeta,changelog,transitions,renderedFields",
        "id": "12926128",
        "self": "https://issues.apache.org/jira/rest/api/2/issue/12926128",
        "key": "APEXMALHAR-1843",
        "fields": {
          "summary": "Split Malhar Library and Malhar Contrib package into baby packages",
          "description": "[~andyp] I am assigning this to you cause you are the one who first said it. So either you lead it or find a willing lead to get this task to completion.\r\n\r\nThe problem with contrib and library modules of malhar is that a ton of dependencies are prescribed as optional. The motive behind it was that the users of these libraries are given an opportunity to keep the size of the dependency-included packages to bare minimum. It  comes at a cost that the dependency now has to be manually figured out. This is a complete misuse of the optional dependency, IMO. It defeats the purpose of maven having dependency management as one of the biggest features of it.\r\n\r\nSo keep things sane - the proposed compromise is that we start creating smaller discreet packages for discrete technologies.",
          "fixVersions": [],
          "priority": {
            "self": "https://issues.apache.org/jira/rest/api/2/priority/2",
            "iconUrl": "https://issues.apache.org/jira/images/icons/priorities/critical.png",
            "name": "Critical",
            "id": "2"
          },
          "status": {
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            "description": "The issue is open and ready for the assignee to start work on it.",
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            }
          }
        }
      },
      {
        "expand": "operations,editmeta,changelog,transitions,renderedFields",
        "id": "12926037",
        "self": "https://issues.apache.org/jira/rest/api/2/issue/12926037",
        "key": "APEXMALHAR-1939",
        "fields": {
          "summary": "Stream API",
          "description": null,
          "fixVersions": [],
          "priority": {
            "self": "https://issues.apache.org/jira/rest/api/2/priority/2",
            "iconUrl": "https://issues.apache.org/jira/images/icons/priorities/critical.png",
            "name": "Critical",
            "id": "2"
          },
          "status": {
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            "description": "The issue is open and ready for the assignee to start work on it.",
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              "key": "new",
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            }
          }
        }
      },
      {
        "expand": "operations,editmeta,changelog,transitions,renderedFields",
        "id": "12924154",
        "self": "https://issues.apache.org/jira/rest/api/2/issue/12924154",
        "key": "APEXMALHAR-1999",
        "fields": {
          "summary": "Running a Storm topology on Apex.",
          "description": "Flink streaming is compatible with Apache Storm interfaces and therefore allows reusing code that was implemented for Storm.\r\nDetails can be found here.\r\nhttps://ci.apache.org/projects/flink/flink-docs-master/apis/storm_compatibility.html\r\nThis jira item can contain tasks for providing similar support in Apex",
          "fixVersions": [],
          "priority": {
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        }
      },
      {
        "expand": "operations,editmeta,changelog,transitions,renderedFields",
        "id": "12985430",
        "self": "https://issues.apache.org/jira/rest/api/2/issue/12985430",
        "key": "APEXMALHAR-2130",
        "fields": {
          "summary": "Scalable windowed storage",
          "description": "This feature is used for supporting windowing.\r\n\r\nThe storage needs to have the following features:\r\n1. Spillable key value storage (integrate with APEXMALHAR-2026)\r\n2. Upon checkpoint, it saves a snapshot for the entire data set with the checkpointing window id.  This should be done incrementally (ManagedState) to avoid wasting space with unchanged data\r\n3. When recovering, it takes the recovery window id and restores to that snapshot\r\n4. When a window is committed, all windows with a lower ID should be purged from the store.\r\n5. It should implement the WindowedStorage and WindowedKeyedStorage interfaces, and because of 2 and 3, we may want to add methods to the WindowedStorage interface so that the implementation of WindowedOperator can notify the storage of checkpointing, recovering and committing of a window.\r\n",
          "fixVersions": [
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          },
          "status": {
            "self": "https://issues.apache.org/jira/rest/api/2/status/4",
            "description": "This issue was once resolved, but the resolution was deemed incorrect. From here issues are either marked assigned or resolved.",
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            "name": "Reopened",
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        }
      },
      {
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        "id": "13006875",
        "self": "https://issues.apache.org/jira/rest/api/2/issue/13006875",
        "key": "APEXMALHAR-2260",
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          "summary": "Python execution for operator logic ",
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