Troubleshooting

This section describes common issues and how to solve them. For email support, contact support@pinecone.io.

I cannot install pip

Version 3 of Python uses pip3. Use the following commands at the command line (the terminal):

pip3 install -U pinecone-client

The matches in the 'Euclidean' index results appear in a different order to the other index types

Euclidean distance works in a different way to the other indexes. When you use metric=‘euclidean’, the most similar results are those with the lowest score.

I'm on the free tier and my indexes have been deleted

Free tier users’ indexes will be deleted after 30 days of inactivity.

To prevent this, you can send any request to Pinecone or log into the Pinecone Console. This will count as activity.

Minimizing latency

Pinecone is deployed in the GCP us-west1 US West (Oregon) region.

To minimize latency when you access Pinecone, consider deploying your application in the same US West (Oregon) region.

Contact us if you need a dedicated deployment in other regions. We currently support AWS and GCP.

If you have slow uploads or high latencies

If you experience slow uploads or high query latencies, it may be because you are accessing Pinecone from your home network.

To improve the performance, switch to a cloud environment. For example: EC2, GCE, Google Colab, GCP AI Platform Notebook, or SageMaker Notebook.

How to increase throughput

To increase throughput (QPS), increase the number of replicas for your index. See performance tuning for more information.

pythoncurl
pinecone.create_index(name='index-name',metric='cosine',replicas=num_replicas)
curl -i -X PATCH \
  https://controller.us-west1-gcp.pinecone.io/databases/indexName \
  -H 'Content-Type: application/json' \
  -H 'Api-Key: YOUR_API_KEY' \
  -d '{
    "replicas": 2
  }'

How to upload >1GB of data

See the Manage Indexes documentation for information on how to specify the number of pods (shards) for your index.

Using p1 pods

We use p1 pods for normal indexes. These store the whole runtime index in memory.

Each p1 pod can store up to 1 GB of data.

As a general guideline, add one p1 pod to your index for every additional 1 GB of data.

pythoncurl
pinecone.create_index(name='index-name',metric='cosine',shards=num_shards)
curl -i -X POST \
  https://controller.us-west1-gcp.pinecone.io/databases \
  -H 'Content-Type: application/json' \
  -H 'Api-Key: YOUR_API_KEY' \
  -d '{
    "name": "example-index-name",
    "dimension": 128,
    "index_type": "approximated",
    "metric": "cosine",
    "replicas": 1,
    "shards": 1,
    "index_config": {
      "k_bits": 512,
      "hybrid": False
    }
  }'

Using s1 pods

We use s1 pods for hybrid indexes. Hybrid indexes store data partially in memory and partially on disk.

Each s1 pod can store up to 5 GB of data.

The s1 pods are priced differently, and they require a Standard account. See pricing for more details.

How secure is Pinecone?

We work hard to earn and maintain that trust by treating security and reliability as a cornerstone of our company and product.

See the Trust & Security page for more information.