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content/learning-paths/cross-platform/zenoh-multinode-ros2/5_zenoh-ex2-storagequery.md

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title: Zenoh Example-2 Storage and Query
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title: Run a Zenoh storage and query example
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Building on the previous pub/sub example, you’ll now explore how Zenoh supports persistent data storage and on-demand querying, a powerful feature for robotics and IIoT applications.
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In a typical warehouse or factory scenario, autonomous robots may periodically publish sensor data such as position, temperature, battery level, and a central system or another robot—may later need to query the latest state of each unit.
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In a typical warehouse or factory scenario, autonomous robots can periodically publish sensor data,such as position, temperature, or battery level—that a central system or peer robot may later need to query.
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Unlike Pub/Sub, which requires live, real-time message exchange, Zenoh's storage and query model enables asynchronous access to data that was published earlier, even if the original publisher is no longer online.
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content/learning-paths/cross-platform/zenoh-multinode-ros2/6_zenoh-ex3-queryable.md

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title: Zenoh Example-3 Computation on Query using Queryable
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title: Run a Zenoh queryable example for edge computation
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The result is shown below:
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![img3 alt-text#center](zenoh_ex3.gif "Figure 3: Computation on Query using Queryable")
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![img3 Zenoh queryable node responding to on-demand queries from a remote device#center](zenoh_ex3.gif "Figure 3: Computation on Query using Queryable")
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The value you receive is generated in real time by the function defined in the queryable handler, not from pre-stored data.
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The value you receive comes not from storage, but from the computation inside the queryable handler.
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### Real-world application: distributed inference and computation
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content/learning-paths/cross-platform/zenoh-multinode-ros2/7_zenoh-querycomp.md

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title: Zenoh Example-4 Dynamic Queryable with Computation
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title: Run a Zenoh queryable with parameterized computation
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