{"_id":"574585e243d4d41700a19dfb","__v":7,"category":{"_id":"56e1c96b2506700e00de6e83","version":"55faeacad0e22017005b8268","__v":38,"pages":["56e1ca17cd6a8d0e00d12163","56e1cb0fe416450e00b9e485","56e1cba3cd6a8d0e00d1216c","56e1cc1ae63f910e00e5986b","56e1d0b0cd6a8d0e00d1217f","56e1d15ce416450e00b9e4a3","56e1d23292bf640e00b55663","56e1d296bc46be0e002af287","56e1d305cd6a8d0e00d1218c","56e1d373e416450e00b9e4ab","56e1d38a92bf640e00b55669","56e1d44dbc46be0e002af28e","56e2cb174cd67e220032d655","56e2cf9c1067950e006a16c8","56e2d5ff3987d729008695a0","56e2ddea8ffe6020004c53b2","56e2df768ffe6020004c53bd","56e2e1201067950e006a16f1","56e2e3888ffe6020004c53c5","56e2e53f1067950e006a1702","56e2e9773987d729008695cf","56e2ec731bffb72b00d0562e","56e2ed25b9c88f2900864aab","56e2f0314cd67e220032d6b9","56e2f3c43987d729008695ed","56e2fc3fb9c88f2900864ad7","56e2fe0d3987d7290086960b","56e30180f1ad030e00e72fa7","56e302c228f99e2000a5ffa6","56e3040c6e602e0e00700af6","56e304c5d46bc30e007bb958","56e30650d46bc30e007bb965","56e307456e602e0e00700b08","56e3086251857d0e008e778d","56e3096251857d0e008e7796","56e30a16d46bc30e007bb973","56e30aafd46bc30e007bb97c","56e30aeb51857d0e008e779f"],"project":"55faeacad0e22017005b8265","sync":{"url":"","isSync":false},"reference":false,"createdAt":"2016-03-10T19:22:19.658Z","from_sync":false,"order":15,"slug":"read-query-vector-services-guide","title":"Read & Query Vector Services Guide"},"project":"55faeacad0e22017005b8265","user":"56267741db1eda0d001c3dbb","version":{"_id":"55faeacad0e22017005b8268","project":"55faeacad0e22017005b8265","__v":32,"createdAt":"2015-09-17T16:31:06.800Z","releaseDate":"2015-09-17T16:31:06.800Z","categories":["55faeacbd0e22017005b8269","55faf550764f50210095078e","55faf5b5626c341700fd9e96","55faf8a7825d5f19001fa386","560052f91503430d007cc88f","560054f73aa0520d00da0b1a","56005aaf6932a00d00ba7c62","56005c273aa0520d00da0b3f","5601ae7681a9670d006d164d","5601ae926811d00d00ceb487","5601aeb064866b1900f4768d","5601aee850ee460d0002224c","5601afa02499c119000faf19","5601afd381a9670d006d1652","561d4c78281aec0d00eb27b6","561d588d8ca8b90d00210219","563a5f934cc3621900ac278c","5665c5763889610d0008a29e","566710a36819320d000c2e93","56ddf6df8a5ae10e008e3926","56e1c96b2506700e00de6e83","56e1ccc4e416450e00b9e48c","56e1ccdfe63f910e00e59870","56e1cd10bc46be0e002af26a","56e1cd21e416450e00b9e48e","56e3139a51857d0e008e77be","573b4f62ef164e2900a2b881","57c9d1335fd8ca0e006308ed","57e2bd9d1e7b7220000d7fa5","57f2b992ac30911900c7c2b6","58adb5c275df0f1b001ed59b","58c81b5c6dc7140f003c3c46"],"is_deprecated":false,"is_hidden":false,"is_beta":false,"is_stable":true,"codename":"v1","version_clean":"1.0.0","version":"1"},"parentDoc":null,"updates":[],"next":{"pages":[],"description":""},"createdAt":"2016-05-25T11:00:50.091Z","link_external":false,"link_url":"","githubsync":"","sync_unique":"","hidden":false,"api":{"results":{"codes":[]},"settings":"","auth":"required","params":[],"url":""},"isReference":false,"order":1,"body":"<h2>Vector Services with Bounding Box</h2>\n1. We want to see *OSM Library and School* vectors that are within a given region. The query setup can be generated in several ways:\n - ingest_source:OSM AND item_type:(Library OR School)\n - ingest_source:OSM AND (item_type:Library OR item_type:School)\n - +ingest_source:OSM +(item_type:Library item_type:School)\nGoing through the user interface, copy/pasting any of the above setups will return the same results.\nIn the API, the query would look similar to the following for a paging call:\n<pre><code>https://vector.geobigdata.io/insight-vector/api/vectors/query/paging?q=ingest_source:OSM AND item_type:(Library OR School)&left=32.3964&right=37.2633&upper=42.631&lower=34.7208&ttl=5m&count=500</code></pre>\n(See [Get Paging ID](doc:vs-query-get-paging-id).)\nUsing the paging ID from the previous call, you would then submit a call to retrieve pages of vector items (this is a POST call):\n<pre><code>https://vector.geobigdata.io/insight-vector/api/vectors/paging</code></pre>\nWhere the paging ID is placed within the body of the call.\n(See [Retrieve Page of Vector Items](doc:vs-retrieve-page-of-vector-items).)\n\n\n2. We want to see all of the *rail and road* vectors available within a given region, including all variations, that were generated *in the last month*.\n - item_date:[now-1M TO now] AND item_type.analyzed:(rail OR road)\n - item_date:[now-1M TO now] AND (item_type.analyzed:rail OR item_type.analyzed:road)\n - +item_date:[now-1M TO now] +(item_type.analyzed:rail item_type.analyzed:road)\nNote that time may be expressed in two ways: using the now format, or using ISO-8601 format. (See [Query Syntax](doc:vector-query-syntax-query-fields-and-type-suffixes).)\nGoing through the user interface, copy/pasting any of the above setups will return the same results.\nIn the API, the query would look similar to the following for a paging call:\n<pre><code>https://vector.geobigdata.io/insight-vector/api/vectors/query/paging?q=item_date:[now-1M TO now] AND (item_type.analyzed:rail OR item_type.analyzed:road)&left=32.3964&right=37.2633&upper=42.631&lower=34.7208&ttl=5m&count=500</code></pre>\n(See [Get Paging ID](doc:vs-query-get-paging-id).)\nUsing the paging ID from the previous call, you would then submit a call to retrieve pages of vector items (this is a POST call):\n<pre><code>https://vector.geobigdata.io/insight-vector/api/vectors/paging</code></pre>\nWhere the paging ID is placed within the body of the call.\n(See [Retrieve Page of Vector Items](doc:vs-retrieve-page-of-vector-items).)\n\n\n3. We want to see *DG Catalog* vectors *within the last 30 days* within a given region. The query setup can be generated in a couple of ways:\n - ingest_source:\\\"DG Catalog\\\" AND item_date:[now-30d TO now]\n - +ingest_source:\\\"DG Catalog\\\" +item_date:[now-30d TO now]\nNote that time may be expressed in two ways: using the now format, or using ISO-8601 format. (See [Query Syntax](doc:vector-query-syntax-query-fields-and-type-suffixes).)\nGoing through the user interface, copy/pasting either of the above setups will return the same results.\nIn the API, first we must make a call to get the paging ID for retrieving our results. The fully constructed query would look similar to the following for a paging ID call (this is a GET call):\n<pre><code>https://vector.geobigdata.io/insight-vector/api/vectors/query/paging?q=ingest_source:\\\"DG Catalog\\\" AND item_date:[now-30d TO now]&left=32.3964&right=37.2633&upper=42.631&lower=34.7208&ttl=5m&count=500</code></pre>\n(See [Get Paging ID](doc:vs-query-get-paging-id).)\nUsing the paging ID from the previous call, you would then submit a call to retrieve pages of vector items (this is a POST call):\n<pre><code>https://vector.geobigdata.io/insight-vector/api/vectors/paging</code></pre>\nWhere the paging ID is placed within the body of the call.\n(See [Retrieve Page of Vector Items](doc:vs-retrieve-page-of-vector-items).)","excerpt":"Query construction for both the UI and the API call that would result","slug":"vs-example-query-constructions","type":"basic","title":"Vector Services Example Query Constructions"}

Vector Services Example Query Constructions

Query construction for both the UI and the API call that would result

<h2>Vector Services with Bounding Box</h2> 1. We want to see *OSM Library and School* vectors that are within a given region. The query setup can be generated in several ways: - ingest_source:OSM AND item_type:(Library OR School) - ingest_source:OSM AND (item_type:Library OR item_type:School) - +ingest_source:OSM +(item_type:Library item_type:School) Going through the user interface, copy/pasting any of the above setups will return the same results. In the API, the query would look similar to the following for a paging call: <pre><code>https://vector.geobigdata.io/insight-vector/api/vectors/query/paging?q=ingest_source:OSM AND item_type:(Library OR School)&left=32.3964&right=37.2633&upper=42.631&lower=34.7208&ttl=5m&count=500</code></pre> (See [Get Paging ID](doc:vs-query-get-paging-id).) Using the paging ID from the previous call, you would then submit a call to retrieve pages of vector items (this is a POST call): <pre><code>https://vector.geobigdata.io/insight-vector/api/vectors/paging</code></pre> Where the paging ID is placed within the body of the call. (See [Retrieve Page of Vector Items](doc:vs-retrieve-page-of-vector-items).) 2. We want to see all of the *rail and road* vectors available within a given region, including all variations, that were generated *in the last month*. - item_date:[now-1M TO now] AND item_type.analyzed:(rail OR road) - item_date:[now-1M TO now] AND (item_type.analyzed:rail OR item_type.analyzed:road) - +item_date:[now-1M TO now] +(item_type.analyzed:rail item_type.analyzed:road) Note that time may be expressed in two ways: using the now format, or using ISO-8601 format. (See [Query Syntax](doc:vector-query-syntax-query-fields-and-type-suffixes).) Going through the user interface, copy/pasting any of the above setups will return the same results. In the API, the query would look similar to the following for a paging call: <pre><code>https://vector.geobigdata.io/insight-vector/api/vectors/query/paging?q=item_date:[now-1M TO now] AND (item_type.analyzed:rail OR item_type.analyzed:road)&left=32.3964&right=37.2633&upper=42.631&lower=34.7208&ttl=5m&count=500</code></pre> (See [Get Paging ID](doc:vs-query-get-paging-id).) Using the paging ID from the previous call, you would then submit a call to retrieve pages of vector items (this is a POST call): <pre><code>https://vector.geobigdata.io/insight-vector/api/vectors/paging</code></pre> Where the paging ID is placed within the body of the call. (See [Retrieve Page of Vector Items](doc:vs-retrieve-page-of-vector-items).) 3. We want to see *DG Catalog* vectors *within the last 30 days* within a given region. The query setup can be generated in a couple of ways: - ingest_source:\"DG Catalog\" AND item_date:[now-30d TO now] - +ingest_source:\"DG Catalog\" +item_date:[now-30d TO now] Note that time may be expressed in two ways: using the now format, or using ISO-8601 format. (See [Query Syntax](doc:vector-query-syntax-query-fields-and-type-suffixes).) Going through the user interface, copy/pasting either of the above setups will return the same results. In the API, first we must make a call to get the paging ID for retrieving our results. The fully constructed query would look similar to the following for a paging ID call (this is a GET call): <pre><code>https://vector.geobigdata.io/insight-vector/api/vectors/query/paging?q=ingest_source:\"DG Catalog\" AND item_date:[now-30d TO now]&left=32.3964&right=37.2633&upper=42.631&lower=34.7208&ttl=5m&count=500</code></pre> (See [Get Paging ID](doc:vs-query-get-paging-id).) Using the paging ID from the previous call, you would then submit a call to retrieve pages of vector items (this is a POST call): <pre><code>https://vector.geobigdata.io/insight-vector/api/vectors/paging</code></pre> Where the paging ID is placed within the body of the call. (See [Retrieve Page of Vector Items](doc:vs-retrieve-page-of-vector-items).)