# Source: https://docs.pinecone.io/release-notes/2022.md

# Source: https://docs.pinecone.io/assistant-release-notes/2022.md

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pinecone.io/llms.txt
> Use this file to discover all available pages before exploring further.

# 2022 releases

## December 22, 2022

#### Pinecone is now available in Google Cloud Marketplace

You can now [sign up for Pinecone billing through Google Cloud Marketplace](/guides/organizations/manage-billing/upgrade-billing-plan).

## December 6, 2022

#### Organizations are generally available

Pinecone now features [organizations](/guides/organizations/understanding-organizations), which allow one or more users to control billing and project settings across multiple projects owned by the same organization.

#### p2 pod type is generally available

The [p2 pod type](/guides/index-data/indexing-overview#p2-pods) is now generally available and ready for production workloads. p2 pods are now available in the Starter plan and support the [dotproduct distance metric](/guides/index-data/create-an-index#dotproduct).

#### Performance improvements

* [Bulk vector\_deletes](/guides/index-data/upsert-data/#deleting-vectors) are now up to 10x faster in many circumstances.
* [Creating collections](/guides/manage-data/back-up-an-index) is now faster.

## October 31, 2022

#### Hybrid search (Early access)

Pinecone now supports keyword-aware semantic search with the new hybrid search indexes and endpoints. Hybrid search enables improved relevance for semantic search results by combining them with keyword search.

This is an **early access** feature and is available only by [signing up](https://www.pinecone.io/hybrid-search-early-access/).

## October 17, 2022

#### Status page

The new [Pinecone Status Page](https://status.pinecone.io/) displays information about the status of the Pinecone service, including the status of individual cloud regions and a log of recent incidents.

## September 16, 2022

#### Public collections

You can now create indexes from public collections, which are collections containing public data from real-world data sources. Currently, public collections include the Glue - SSTB collection, the TREC Question classification collection, and the SQuAD collection.

## August 16, 2022

#### Collections (Public preview)("Beta")

You can now \[make static copies of your index]\(/guides/manage-data/back-up-an-index using collections]\(/guides/manage-data/back-up-an-index#pod-based-index-backups-using-collections). After you create a collection from an index, you can create a new index from that collection. The new index can use any pod type and any number of pods. Collections only consume storage.

This is a **public preview** feature and is not appropriate for production workloads.

#### Vertical scaling

You can now [change the size of the pods](/guides/indexes/pods/scale-pod-based-indexes#increase-pod-size) for a live index to accommodate more vectors or queries without interrupting reads or writes. The p1 and s1 pod types are now available in [4 different sizes](/guides/index-data/indexing-overview/#pods-pod-types-and-pod-sizes): `1x`, `2x`, `4x`, and `8x`. Capacity and compute per pod double with each size increment.

#### p2 pod type (Public preview)("Beta")

The new [p2 pod type](/guides/index-data/indexing-overview/#p2-pods) provides search speeds of around 5ms and throughput of 200 queries per second per replica, or approximately 10x faster speeds and higher throughput than the p1 pod type, depending on your data and network conditions.

This is a **public preview** feature and is not appropriate for production workloads.

#### Improved p1 and s1 performance

The [s1](/guides/index-data/indexing-overview/#s1-pods) and [p1](/guides/index-data/indexing-overview/#p1-pods) pod types now offer approximately 50% higher query throughput and 50% lower latency, depending on your workload.

## July 26, 2022

You can now specify a [metadata filter](/guides/index-data/indexing-overview#metadata/) to get results for a subset of the vectors in your index by calling [describe\_index\_stats](/reference/api/2024-07/control-plane/describe_index) with a [filter](/reference/api/2024-07/control-plane/describe_index#!path=filter\&t=request) object.

The `describe_index_stats` operation now uses the `POST` HTTP request type. The `filter` parameter is only accepted by `describe_index_stats` calls using the `POST` request type. Calls to `describe_index_stats` using the `GET` request type are now deprecated.

## July 12, 2022

#### Pinecone Console Guided Tour

You can now choose to follow a guided tour in the [Pinecone console](https://app.pinecone.io). This interactive tutorial walks you through creating your first index, upserting vectors, and querying your data. The purpose of the tour is to show you all the steps you need to start your first project in Pinecone.

## June 24, 2022

#### Updated response codes

The [create\_index](/reference/api/2024-07/control-plane/create_index), [delete\_index](/reference/api/2024-07/control-plane/delete_index), and `scale_index` operations now use more specific HTTP response codes that describe the type of operation that succeeded.

## June 7, 2022

#### Selective metadata indexing

You can now store more metadata and more unique metadata values! [Select which metadata fields you want to index for filtering](/guides/indexes/pods/manage-pod-based-indexes#selective-metadata-indexing) and which fields you only wish to store and retrieve. When you index metadata fields, you can filter vector search queries using those fields. When you store metadata fields without indexing them, you keep memory utilization low, especially when you have many unique metadata values, and therefore can fit more vectors per pod.

#### Single-vector queries

You can now [specify a single query vector using the vector input](/reference/api/2024-07/data-plane/query/#!path=vector\&t=request). We now encourage all users to query using a single vector rather than a batch of vectors, because batching queries can lead to long response messages and query times, and single queries execute just as fast on the server side.

#### Query by ID

You can now [query your Pinecone index using only the ID for another vector](/reference/api/2024-07/data-plane/query/#!path=id\&t=request). This is useful when you want to search for the nearest neighbors of a vector that is already stored in Pinecone.

#### Improved index fullness accuracy

The index fullness metric in [describe\_index\_stats()](/reference/api/2024-07/control-plane/describe_index#!c=200\&path=indexFullness\&t=response) results is now more accurate.

## April 25, 2022

#### Partial updates (Public preview)

You can now perform a partial update by ID and individual value pairs. This allows you to update individual metadata fields without having to upsert a matching vector or update all metadata fields at once.

#### New metrics

Users on all plans can now see metrics for the past one (1) week in the Pinecone console. Users on the Enterprise plan now have access to the following metrics via the [Prometheus metrics endpoint](/guides/production/monitoring/):

* `pinecone_vector_count`
* `pinecone_request_count_total`
* `pinecone_request_error_count_total`
* `pinecone_request_latency_seconds`
* `pinecone_index_fullness` (Public preview)

**Note:** The accuracy of the `pinecone_index_fullness` metric is improved. This may result in changes from historic reported values. This metric is in public preview.

#### Spark Connector

Spark users who want to manage parallel upserts into Pinecone can now use the [official Spark connector for Pinecone](https://github.com/pinecone-io/spark-pinecone#readme) to upsert their data from a Spark dataframe.

#### Support for Boolean and float metadata in Pinecone indexes

You can now add `Boolean` and `float64` values to [metadata JSON objects associated with a Pinecone index.](/guides/index-data/indexing-overview#metadata)

#### New state field in describe\_index results

The [describe\_index](/reference/api/2024-07/control-plane/describe_index/) operation results now contain a value for `state`, which describes the state of the index. The possible values for `state` are `Initializing`, `ScalingUp`, `ScalingDown`, `Terminating`, and `Ready`.

##### Delete by metadata filter

The [Delete](/reference/api/2024-07/data-plane/delete/) operation now supports filtering my metadata.